WO2024027683A1 - Model matching method and apparatus, communication device, and readable storage medium - Google Patents
Model matching method and apparatus, communication device, and readable storage medium Download PDFInfo
- Publication number
- WO2024027683A1 WO2024027683A1 PCT/CN2023/110481 CN2023110481W WO2024027683A1 WO 2024027683 A1 WO2024027683 A1 WO 2024027683A1 CN 2023110481 W CN2023110481 W CN 2023110481W WO 2024027683 A1 WO2024027683 A1 WO 2024027683A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- model
- data set
- channel
- information
- channel information
- Prior art date
Links
- 238000000034 method Methods 0.000 title claims abstract description 111
- 238000004891 communication Methods 0.000 title claims abstract description 32
- 238000012545 processing Methods 0.000 claims abstract description 18
- 230000008569 process Effects 0.000 claims description 47
- 230000002452 interceptive effect Effects 0.000 claims 1
- 238000012549 training Methods 0.000 abstract description 2
- 230000006870 function Effects 0.000 description 39
- 238000010586 diagram Methods 0.000 description 12
- 238000013528 artificial neural network Methods 0.000 description 10
- 230000000694 effects Effects 0.000 description 9
- 238000007726 management method Methods 0.000 description 9
- 238000005516 engineering process Methods 0.000 description 7
- 210000002569 neuron Anatomy 0.000 description 7
- 238000005457 optimization Methods 0.000 description 7
- 238000004590 computer program Methods 0.000 description 6
- 230000001360 synchronised effect Effects 0.000 description 5
- 230000003044 adaptive effect Effects 0.000 description 4
- 230000005540 biological transmission Effects 0.000 description 3
- 230000004913 activation Effects 0.000 description 2
- 238000013473 artificial intelligence Methods 0.000 description 2
- 230000007774 longterm Effects 0.000 description 2
- 239000011159 matrix material Substances 0.000 description 2
- 230000011664 signaling Effects 0.000 description 2
- 230000003068 static effect Effects 0.000 description 2
- ORILYTVJVMAKLC-UHFFFAOYSA-N Adamantane Natural products C1C(C2)CC3CC1CC2C3 ORILYTVJVMAKLC-UHFFFAOYSA-N 0.000 description 1
- 241000699670 Mus sp. Species 0.000 description 1
- 239000000654 additive Substances 0.000 description 1
- 230000000996 additive effect Effects 0.000 description 1
- 230000003190 augmentative effect Effects 0.000 description 1
- 230000006835 compression Effects 0.000 description 1
- 238000007906 compression Methods 0.000 description 1
- 238000012937 correction Methods 0.000 description 1
- 238000013523 data management Methods 0.000 description 1
- 238000003066 decision tree Methods 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000007599 discharging Methods 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 239000004973 liquid crystal related substance Substances 0.000 description 1
- 238000003062 neural network model Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000011084 recovery Methods 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 230000002441 reversible effect Effects 0.000 description 1
- 239000004984 smart glass Substances 0.000 description 1
- 238000012706 support-vector machine Methods 0.000 description 1
- 238000005406 washing Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/045—Combinations of networks
- G06N3/0455—Auto-encoder networks; Encoder-decoder networks
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
- G06N3/084—Backpropagation, e.g. using gradient descent
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
- G06N3/0985—Hyperparameter optimisation; Meta-learning; Learning-to-learn
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B17/00—Monitoring; Testing
- H04B17/30—Monitoring; Testing of propagation channels
- H04B17/391—Modelling the propagation channel
Definitions
- This application belongs to the field of communication technology, and specifically relates to a model matching method, device, communication equipment and readable storage medium.
- model-based channel information feedback includes a coding part on the terminal side and a decoding part on the base station side.
- the coding part and the decoding part are jointly trained and match each other.
- the base station and the terminal need to independently train their respective required models. In this case, the coding model on the terminal side and the decoding model on the base station side will not match, and the output of the coding model on the terminal side cannot be restored through the decoding model on the base station side, affecting channel information feedback.
- Embodiments of the present application provide a model matching method, device, communication equipment and readable storage medium, which can solve the problem in related technologies that the models on the terminal side and the network side cannot be matched.
- the first aspect provides a model matching method, including:
- the first device acquires first channel characteristic information, which is obtained by the second device using the first model to process the first channel information
- the first device matches the second model of the first device with the first model according to the first channel characteristic information and the second channel information corresponding to the first channel characteristic information;
- the first channel information is the same as the second channel information; the first model and the second model are models trained in different devices; when the first device is a network side device, the When the second device is a terminal, the second model is used to process the channel characteristic information obtained by the first device; or when the first device is a terminal and the second device is a network side device , the second model is used to process channel information.
- a model matching device including:
- An acquisition module configured to acquire first channel characteristic information, which is obtained by processing the first channel information by the second device using the first model
- a matching module configured to match the second model of the first device with the first model according to the first channel characteristic information and the second channel information corresponding to the first channel characteristic information
- the first channel information and the second channel information are the same; the first model and the second model are Models trained in different devices; when the first device is a network-side device and the second device is a terminal, the second model is used to process the channel characteristic information obtained by the first device; Or, when the first device is a terminal and the second device is a network-side device, the second model is used to process channel information.
- a communication device in a third aspect, includes a processor and a memory.
- the memory stores a program or instructions that can be run on the processor.
- the program or instructions are implemented when executed by the processor. The steps of the method as described in the first aspect.
- a communication device is provided.
- the communication device is a first device and includes a processor and a communication interface.
- the processor is used to obtain first channel characteristic information.
- the first channel characteristic information is used by the second device.
- the first model is obtained by processing the first channel information; according to the first channel characteristic information and the second channel information corresponding to the first channel characteristic information, the second model of the first device and the third A model is used for matching; the first channel information is the same as the second channel information; the first model and the second model are models trained in different devices; when the first device is a network side device, when the second device is a terminal, the second model is used to process the channel characteristic information obtained by the first device; or, when the first device is a terminal, the second device is a network When a side device is used, the second model is used to process channel information.
- a communication system including: a first device and a second device.
- the first device can be used to perform the steps of the model matching method as described in the first aspect.
- the second device can utilize the second device.
- a model processes the first channel information, obtains first channel characteristic information, and sends the first channel characteristic information to the first device.
- a readable storage medium is provided. Programs or instructions are stored on the readable storage medium. When the programs or instructions are executed by a processor, the steps of the method described in the first aspect are implemented.
- a chip in a seventh aspect, includes a processor and a communication interface.
- the communication interface is coupled to the processor.
- the processor is used to run programs or instructions to implement the method described in the first aspect. A step of.
- a computer program/program product is provided, the computer program/program product is stored in a storage medium, and the computer program/program product is executed by at least one processor to implement the method described in the first aspect Method steps.
- the first channel characteristic information is obtained by the second device using the first model to process the first channel information
- the first channel characteristic information is obtained according to the first channel characteristic information and the first channel characteristic information.
- the second channel information corresponding to the channel characteristic information matches the second model of the first device with the first model, so that the first model and the second model that are independently trained can be matched, so that the channel processed by the terminal side model Characteristic information can be recovered through the network side model to obtain corresponding channel information, thereby ensuring channel information feedback.
- Figure 1 is a block diagram of a wireless communication system applicable to the embodiment of the present application.
- Figure 2 is a schematic diagram of a neural network in an embodiment of the present application.
- FIG. 3 is a schematic diagram of neurons in the embodiment of the present application.
- Figure 4 is a flow chart of a model matching method provided by an embodiment of the present application.
- Figure 5 is a schematic structural diagram of a model matching device provided by an embodiment of the present application.
- Figure 6 is a schematic structural diagram of a communication device provided by an embodiment of the present application.
- Figure 7 is a schematic structural diagram of a terminal provided by an embodiment of the present application.
- Figure 8 is a schematic structural diagram of a network side device provided by an embodiment of the present application.
- first, second, etc. in the description and claims of this application are used to distinguish similar objects and are not used to describe a specific order or sequence. It is to be understood that the terms so used are interchangeable under appropriate circumstances so that the embodiments of the present application can be practiced in sequences other than those illustrated or described herein, and that "first" and “second” are distinguished objects It is usually one type, and the number of objects is not limited.
- the first object can be one or multiple.
- “and/or” in the description and claims indicates at least one of the connected objects, and the character “/" generally indicates that the related objects are in an "or” relationship.
- LTE Long Term Evolution
- LTE-Advanced, LTE-A Long Term Evolution
- LTE-A Long Term Evolution
- CDMA Code Division Multiple Access
- TDMA Time Division Multiple Access
- FDMA Frequency Division Multiple Access
- OFDMA Orthogonal Frequency Division Multiple Access
- SC-FDMA Single-carrier Frequency Division Multiple Access
- NR New Radio
- FIG. 1 shows a block diagram of a wireless communication system to which embodiments of the present application are applicable.
- the wireless communication system includes a terminal 11 and a network side device 12.
- the terminal 11 may be a mobile phone, a tablet computer (Tablet Personal Computer), a laptop computer (Laptop Computer), or a notebook computer, a personal digital assistant (Personal Digital Assistant, PDA), a palmtop computer, a netbook, or a super mobile personal computer.
- Tablet Personal Computer Tablet Personal Computer
- laptop computer laptop computer
- PDA Personal Digital Assistant
- PDA Personal Digital Assistant
- UMPC ultra-mobile personal computer
- UMPC mobile Internet device
- MID mobile Internet Device
- AR augmented reality
- VR virtual reality
- robots wearable devices
- WUE Vehicle User Equipment
- PUE Pedestrian User Equipment
- smart home home equipment with wireless communication functions, such as refrigerators, TVs, washing machines or furniture, etc.
- game consoles personal computers (personal computer, PC), teller machine or self-service machine and other terminal-side equipment.
- Wearable devices include: smart watches, smart bracelets, smart headphones, smart glasses, smart jewelry (smart bracelets, smart bracelets, smart rings, smart Necklaces, smart anklets, smart anklets, etc.), smart wristbands, smart clothing, etc.
- the network side device 12 may include an access network device or a core network device, where the access network device may also be called a radio access network device, a radio access network (Radio Access Network, RAN), a radio access network function or a wireless access network unit.
- Access network equipment may include a base station, a Wireless Local Area Network (WLAN) access point or a WiFi node, etc.
- the base station may be called a Node B, an Evolved Node B (eNB), an access point, or a base station.
- BTS Base Transceiver Station
- BSS Basic Service Set
- ESS Extended Service Set
- TRP Transmitting Receiving Point
- the base station is not limited to specific technical terms. It should be noted that in the embodiment of this application, only The base station in the NR system is taken as an example for introduction, and the specific type of base station is not limited.
- Core network equipment may include but is not limited to at least one of the following: core network nodes, core network functions, mobility management entities (Mobility Management Entity, MME), access mobility management functions (Access and Mobility Management Function, AMF), session management functions (Session Management Function, SMF), User Plane Function (UPF), Policy Control Function (PCF), Policy and Charging Rules Function (PCRF), Edge Application Service Discovery function (Edge Application Server Discovery Function, EASDF), Unified Data Management (UDM), Unified Data Repository (UDR), Home Subscriber Server (HSS), centralized network configuration ( Centralized network configuration (CNC), Network Repository Function (NRF), Network Exposure Function (NEF), Local NEF (Local NEF, or L-NEF), Binding Support Function (Binding Support Function, BSF), application function (Application Function, AF), etc.
- MME mobility management entities
- AMF Access and Mobility Management Function
- SMF Session Management Function
- UPF User Plane Function
- PCF Policy Control Function
- the model in the embodiment of this application may be an artificial intelligence (Artificial Intelligence, AI) model.
- AI models have a variety of algorithm implementations, such as neural networks, decision trees, support vector machines, Bayesian classifiers, etc. This application takes neural network as an example for explanation, but does not limit the specific type of AI module.
- the schematic diagram of a neural network can be shown in Figure 2, in which X 1 , The results will continue to be passed to the next layer.
- the input layer, hidden layer and output layer composed of these many neurons is a neural network.
- the number of hidden layers and the number of neurons in each layer is the "network structure" of the neural network.
- a neural network is composed of neurons, and the schematic diagram of the neurons can be shown in Figure 3, where a 1 , a k ...a K (i.e., X1, X2... shown in Figure 2) are inputs, and w is the weight. (can also be called: multiplicative coefficient), b is the bias (can also be called: additive coefficient), ⁇ () is the activation function, z is the output value, and the corresponding operation process can be expressed as: Common activation functions include but are not limited to Sigmoid function, hyperbolic tanh function, rectified linear unit (Rectified Linear Unit, ReLU), etc.
- the parameter information of each neuron and the algorithm used are combined to form the "parameter information" of the entire neural network, which is also an important part of the AI model file.
- the parameters of neural networks can be optimized through optimization algorithms.
- An optimization algorithm is a type of algorithm that can minimize or maximize an objective function (sometimes also called a loss function).
- the objective function is often a mathematical combination of model parameters and data. For example, given data x and its corresponding label Y, and constructing a neural network model f(.), with the model, the predicted output f(x) can be obtained based on the input data x, and the predicted value and the true value can be calculated The difference between the values (f(x)-Y), this is the loss function.
- the purpose at this time is to find appropriate model parameters (such as weights/biases) to minimize the value of the above loss function. The smaller the loss value, the closer the model is to the real situation.
- the optimization algorithm includes error back propagation (error Back Propagation, BP) algorithm.
- error Back Propagation BP
- the basic idea of BP algorithm is that the learning process consists of two processes: forward propagation of signals and back propagation of errors.
- the back propagation of error is to back propagate the output error in some form to the input layer layer by layer through the hidden layer, and allocate the error to all units in each layer, thereby obtaining the error signal of each layer unit, and this error signal is used as a correction The basis for the weight of each unit.
- This process of adjusting the weights of each layer in forward signal propagation and error back propagation is carried out over and over again.
- the process of continuous adjustment of weights is the learning and training process of the neural network. This process continues until the error of the network output is reduced to an acceptable level, or until a preset number of learning times.
- optimization algorithms may include but are not limited to: gradient descent (Gradient Descent), stochastic gradient descent (Stochastic Gradient Descent, SGD), mini-batch gradient descent (mini-batch gradient descent), momentum method (Momentum), driven momentum Stochastic gradient descent (such as Nesterov), adaptive gradient descent (ADAptive GRADient descent, Adagrad), Adadelta algorithm, root mean square error reduction (root mean square prop, RMSprop), adaptive momentum estimation (Adaptive Moment Estimation, Adam) wait.
- gradient descent Gradient Descent
- stochastic gradient descent stochastic gradient descent
- mini-batch gradient descent mini-batch gradient descent
- momentum method Motionum
- driven momentum Stochastic gradient descent such as Nesterov
- adaptive gradient descent ADAptive GRADient descent, Adagrad
- Adadelta algorithm root mean square error reduction (root mean square prop, RMSprop), adaptive momentum estimation (Adaptive Moment Estimation, Adam) wait.
- the function of the encoding network (or coding model) is to compress channel information into channel characteristic information
- the function of the decoding network (or called decoding model) is to restore the channel characteristic information into corresponding channel information. Therefore
- the compression method of the encoding network and the recovery method of the decoding network need to match each other.
- the base station and the terminal since models with good performance often have relatively large model sizes and high transmission overhead, and the base station and the terminal may not want the other party to know the model they use and the optimization processing, the base station and the terminal can independently train the required model.
- Figure 4 is a flow chart of a model matching method provided by an embodiment of the present application.
- the method is applied to a first device.
- the first device can be a terminal or a network side device.
- the network side device For example, it is a base station or core network equipment.
- the method includes the following steps:
- Step 41 The first device obtains the first channel characteristic information.
- the first channel characteristic information is used by the second device.
- the first model is obtained by processing the first channel information.
- Step 42 The first device matches the second model of the first device with the first model according to the first channel characteristic information and the second channel information corresponding to the first channel characteristic information.
- the above-mentioned first model and second model are models trained on different devices.
- the second model is used to process the channel characteristic information obtained by the first device (i.e., network-side device, such as a base station); or, when the first device is a terminal , when the second device is a network-side device, the second model is used to process channel information.
- the above-mentioned first channel information and the second channel information are the same, that is to say, the first channel information and the second channel information are the same channel information located in the second device and the first device respectively, and one is used for the first device.
- One model processes the first channel information, and the other is used for model matching.
- the above-mentioned first channel characteristic information may be obtained by the second device using the first model to encode/compress the first channel information.
- the first model can be understood as a coding model trained in the second device.
- the above processing of the channel characteristic information obtained by the first device can be understood as decoding/decompressing the channel characteristic information.
- the above processing of channel information can be understood as encoding/compressing the channel information.
- the above-mentioned first channel information/second channel information may be, but is not limited to, a channel matrix, a precoding matrix, etc.
- the first model is a coding model trained in the terminal for encoding channel information
- the second model is a coding model trained in the network-side device.
- a decoding model used to decode the acquired channel characteristic information.
- the encoding result of the channel information in the first model of the terminal is used as the input of the network-side decoding model, and this channel information is used as the output of the decoding model, and the decoding model can be trained.
- the encoding model and the decoding model trained separately are matched, so that the channel characteristic information encoded by the terminal-side encoding model can be decoded by the network-side encoding model to obtain the corresponding channel information, thereby ensuring channel information feedback.
- the first model is a coding model trained in the network-side device for encoding channel information
- the second model is a coding model trained in the terminal. Coding model used to encode channel information. Since the encoding model and decoding model trained by the network side device match the channel information, and the encoding model and decoding model trained by the terminal match, therefore, by matching the second model with the first model, the network side device can The trained coding model matches the coding model trained by the terminal, so that the channel characteristic information encoded by the terminal-side coding model can be decoded by the network-side coding model to obtain the corresponding channel information, thereby ensuring channel information feedback.
- the model matching method in the embodiment of the present application obtains the first channel characteristic information, which is obtained by the second device using the first model to process the first channel information, and based on the first channel characteristic information and the The second channel information corresponding to the first channel characteristic information matches the second model of the first device with the first model, so that the first model and the second model that are independently trained can be matched, so that the terminal side model processes the
- the channel characteristic information can be recovered through the network side model to obtain the corresponding channel information, thereby ensuring channel information feedback.
- model transmission can be avoided, thereby saving overhead and meeting the requirements of Network-side devices and terminals do not want the other party to know the model they are using and the need for corresponding optimization processing.
- the first device may receive an identifier of the second channel information, and then determine the characteristics of the first channel based on the identifier of the second channel information.
- the second channel information corresponding to the information is used to perform model matching based on the first channel characteristic information and the corresponding second channel information.
- the base station sends indication information to instruct the terminal on the time, period, etc. to report matching information; then, the terminal determines the corresponding time based on the indication information or calculates the corresponding time based on the indicated period.
- the matching information is reported on the configured time-frequency resources, including the first channel characteristic information and the identification (Identity, ID) of the corresponding channel information in the first data set.
- This ID is used as the second channel information. identification; then, after receiving the ID, the base station finds the corresponding second channel information in the first data set.
- the first device may determine the second model corresponding to the first channel characteristic information based on the obtained time-frequency domain position of the first channel characteristic information.
- Channel information to perform model matching based on the first channel characteristic information and the corresponding second channel information For example, the terminal can send channel characteristic information at a designated time-frequency domain position, and the base station determines channel information corresponding to the channel characteristic information based on the time-frequency domain position.
- the above time-frequency domain position can be configured by the network side.
- the base station configures the time-frequency domain location for the terminal to send channel characteristic information.
- the above-mentioned first channel information and second channel information may be channel information in a first data set, and the channel information in the first data set is used for model matching. That is, the terminal and the network side device can perform model processing based on the same first data set containing channel information.
- the first data set may be referred to as a matching data set.
- the terminal generates the corresponding coding result, that is, channel characteristic information, based on the channel information in the matching data set.
- the terminal sends the channel characteristic information to the base station.
- the base station codes the terminal's coding model based on the channel information in the matching data set and the corresponding channel characteristic information. Make a match.
- the terminal can use data set A to train a channel state information (CSI) compressed AI model, including a coding model and a decoding model
- the base station can use data set B to train a CSI compressed AI model, including a coding model. and decoding models.
- data set A and data set B can be the same or different.
- the matching data set used by the further model matching process can be different from both data set A and data set B.
- the order of the first channel information and the second channel information in the channel information contained in the first data set may be agreed by the protocol or configured by the network side.
- the order of the first channel information and the second channel information in the channel information contained in the first data set is fixed.
- the first device may receive the first data set from the second device.
- the first data set can be sent by the base station to the terminal in real time.
- the terminal encodes certain channel information in the received first data set to obtain the channel characteristic information and feeds it back to the base station.
- the base station then codes based on the channel characteristic information and the corresponding channel. information for model matching.
- the first data set may be measured by the terminal in real time.
- the terminal sends the estimated channel information and the encoded channel characteristic information to the base station, and the base station performs model matching based on the channel characteristic information and corresponding channel information.
- the above-mentioned first data set can satisfy at least one of the following:
- the third device may be understood as an independent device, an independent node, etc.
- the terminal may receive configuration information of the network side device, where the configuration information is used to configure the third data set.
- An identifier of a data set select the first data set from the second data set according to the identifier of the first data set.
- the range of the second data set is agreed upon by the protocol and divided into multiple subsets, and the base station selects and instructs the terminal to use the subset (ie, the first data set).
- the second data set may be agreed upon in a protocol, or may be collected or updated by a third device different from the first device and the second device.
- the collection and/or updating of the second data set may be offline or long-term.
- the network side equipment such as the base station can indicate in the second data set that part of it is the first data set.
- the indication information can be downlink control information (Downlink Control Information, DCI), medium access control control element (Medium Access Control Control Element, MAC). CE) or Radio Resource Control (Radio Resource Control, RRC) signaling, etc.
- the first device may perform any of the following: communicate with the second device and/or Or the third device interacts with the updated version of the first data set, interacts with the second device and/or the third device with the updated first data set; and uses the updated first data set to perform model matching. And/or, after the first data set is updated, the updated first data set and/or the updated version of the first data set may be interacted between the third device and the second device. That is to say, after the third device updates the first data set, the third device can notify the first device and/or the second device of the updated first data set through interaction with the first device and/or the second device. , and the first device and the second device can also interact with the updated first data set.
- the base station and the terminal may exchange the updated version of the first data set through signaling to use the same version of the first data set for model matching.
- the third device can periodically update the first data set and send it to the first device and/or the second device.
- the first data set can be sent via the data plane.
- the first device may perform any of the following: communicate with the second device and/or or the third device interacts with the updated version of the second data set, and interacts with the second device and/or the third device with the updated second data set. And/or, after the second data set is updated, the updated second data set and/or a version of the updated second data set may be interacted between the third device and the second device.
- the third device can communicate with the first device
- the first device and/or the second device may interact with each other to inform the first device and/or the second device of the updated second data set, and the first device and the second device may also interact with the updated second data set.
- the above-mentioned matching of the second model of the first device with the first model may include at least one of the following:
- the first device uses the first channel characteristic information as the input of the second model, uses the second channel information as the output of the second model, and retrains the second model;
- the first device adjusts the parameters of the second model according to the first channel characteristic information and the second channel information.
- the output of the first model can be used as the input of the second model (such as decoding model/decoder).
- Train a second model eg, decoding model/decoder
- parameters of the second model eg, decoding model/decoder
- the first model and the second model that are independently trained can be matched, so that the channel characteristic information processed by the terminal side model can be passed through the network side.
- the model is restored to obtain corresponding channel information, thereby ensuring channel information feedback.
- the above-mentioned matching of the second model of the first device with the first model may include at least one of the following:
- the first device uses the first channel characteristic information as the output of the second model, uses the second channel information as the input of the second model, and retrains the second model;
- the first device adjusts the parameters of the second model according to the first channel characteristic information and the second channel information.
- the inputs of the first model (such as encoding model/encoder) and the second model (such as encoding model/encoder) are the same channel information, and the second model can be trained by model (such as encoding model/encoder) or adjust the second model (such as encoding model/encoder) so that the output result of this second model (such as encoding model/encoder) is consistent with the first model (such as encoding model/encoder) )'s output results match, that is, they are the same.
- the first model and the second model that are independently trained can be matched, so that the channel characteristic information processed by the terminal side model can be passed through the network side.
- the model is restored to obtain corresponding channel information, thereby ensuring channel information feedback.
- the execution subject may be a model matching device.
- the model matching device executing the model matching method is used as an example to illustrate the model matching device provided by the embodiment of the present application.
- Figure 5 is a schematic structural diagram of a model matching device provided by an embodiment of the present application.
- the device is applied to a first device.
- the first device can be a terminal or a network side device.
- the network side device is, for example, Base station or core network equipment.
- the model matching device 50 includes:
- the acquisition module 51 is used to obtain the first channel characteristic information, which is obtained by the second device using the first model to process the first channel information;
- Matching module 52 configured to match the first channel characteristic information and the first channel characteristic information corresponding to the first channel characteristic information.
- second channel information matching the second model of the first device with the first model;
- the first channel information is the same as the second channel information; the first model and the second model are models trained in different devices; when the first device is a network side device, the When the second device is a terminal, the second model is used to process the channel characteristic information obtained by the first device; or when the first device is a terminal and the second device is a network side device , the second model is used to process channel information.
- model matching device 50 also includes:
- a first receiving module configured to receive the identification of the second channel information
- a first determination module configured to determine the second channel information corresponding to the first channel characteristic information according to the identification of the second channel information.
- model matching device 50 also includes:
- the second determination module is configured to determine the second channel information corresponding to the first channel characteristic information according to the time-frequency domain position of the first channel characteristic information.
- the time-frequency domain position is configured by the network side.
- the first channel information and the second channel information are channel information in a first data set, and the channel information in the first data set is used for model matching.
- the order of the first channel information and the second channel information in the channel information contained in the first data set is agreed upon by the protocol or configured by the network side.
- model matching device 50 also includes:
- a second receiving module configured to receive the first data set from the second device.
- the first data set satisfies at least one of the following:
- a third device different from the first device and the second device.
- the model matching device 50 when the first data set is a subset of the second data set indicated by the network side device, and if the first device is a terminal, the model matching device 50 further includes:
- a third receiving module configured to receive configuration information of the network side device, where the configuration information is used to configure the identification of the first data set;
- a selection module configured to select the first data set from the second data set according to the identification of the first data set.
- the model matching device 50 when the first data set is provided by a third device different from the first device and the second device, the model matching device 50 further includes:
- a first execution model configured to perform any of the following after the first data set is updated: interact with the updated version of the first data set with the second device and/or the third device, interact with the The second device and/or the third device communicate The first data set after mutual updates;
- the matching module 52 is also configured to perform model matching using the updated first data set.
- the updated first data set and/or the updated version of the first data set may be interacted between the third device and the second device.
- the model matching device 50 when the second data set is provided by a third device different from the first device and the second device, the model matching device 50 further includes:
- a second execution model configured to perform any of the following after the second data set is updated: interact with the updated version of the second data set with the second device and/or the third device; The second device and/or the third device interact with the updated second data set.
- the updated second data set and/or the updated version of the second data set may be interacted between the third device and the second device.
- the matching module 52 is used for at least one of the following:
- the matching module 52 is used for at least one of the following:
- the model matching device 50 provided by the embodiment of the present application can implement each process implemented by the method embodiment in Figure 4 and achieve the same technical effect. To avoid duplication, details will not be described here.
- this embodiment of the present application also provides a communication device 60, which includes a processor 61 and a memory 62.
- the memory 62 stores programs or instructions that can be run on the processor 61.
- the communication device 60 may be a terminal or a network side device, such as a base station or a core network device.
- An embodiment of the present application also provides a communication device.
- the communication device is a first device and includes a processor and a communication interface.
- the processor is configured to obtain first channel characteristic information.
- the first channel characteristic information is obtained by the second device using the first
- the model is obtained by processing the first channel information; according to the first channel characteristic information and the second channel information corresponding to the first channel characteristic information, the second model of the first device and the first model are Matching is performed; the first channel information is the same as the second channel information; the first model and the second model are models trained in different devices; when the first device is a network side device, When the second device is a terminal, the second model is used to process the channel characteristic information obtained by the first device; or when the first device is a terminal, the second device is a network When using a network side device, the second model is used to process channel information.
- This embodiment corresponds to the above-mentioned method embodiment.
- Each implementation process and implementation manner of the above-mentioned method embodiment can be applied to this embodiment
- FIG. 7 is a schematic diagram of the hardware structure of a terminal that implements an embodiment of the present application.
- the terminal 700 includes but is not limited to: a radio frequency unit 701, a network module 702, an audio output unit 703, an input unit 704, a sensor 705, a display unit 706, a user input unit 707, an interface unit 708, a memory 709, a processor 710, etc. At least some parts.
- the terminal 700 may also include a power supply (such as a battery) that supplies power to various components.
- the power supply may be logically connected to the processor 710 through a power management system, thereby managing charging, discharging, and power consumption through the power management system. Management and other functions.
- the terminal structure shown in FIG. 7 does not constitute a limitation on the terminal.
- the terminal may include more or fewer components than shown in the figure, or some components may be combined or arranged differently, which will not be described again here.
- the input unit 704 may include a graphics processing unit (Graphics Processing Unit, GPU) 7041 and a microphone 7042.
- the graphics processor 7041 is responsible for the image capture device (GPU) in the video capture mode or the image capture mode. Process the image data of still pictures or videos obtained by cameras (such as cameras).
- the display unit 706 may include a display panel 7061, which may be configured in the form of a liquid crystal display, an organic light emitting diode, or the like.
- the user input unit 707 includes a touch panel 7071 and at least one of other input devices 7072 .
- Touch panel 7071 also called touch screen.
- the touch panel 7071 may include two parts: a touch detection device and a touch controller.
- Other input devices 7072 may include but are not limited to physical keyboards, function keys (such as volume control keys, switch keys, etc.), trackballs, mice, and joysticks, which will not be described again here.
- the radio frequency unit 701 after receiving downlink data from the network side device, can transmit it to the processor 710 for processing; in addition, the radio frequency unit 701 can send uplink data to the network side device.
- the radio frequency unit 701 includes, but is not limited to, an antenna, amplifier, transceiver, coupler, low noise amplifier, duplexer, etc.
- Memory 709 may be used to store software programs or instructions as well as various data.
- the memory 709 may mainly include a first storage area for storing programs or instructions and a second storage area for storing data, wherein the first storage area may store an operating system, an application program or instructions required for at least one function (such as a sound playback function, Image playback function, etc.) etc.
- memory 709 may include volatile memory or non-volatile memory, or memory 709 may include both volatile and non-volatile memory.
- the non-volatile memory can be read-only memory (Read-Only Memory, ROM), programmable read-only memory (Programmable ROM, PROM), erasable programmable read-only memory (Erasable PROM, EPROM), electrically removable memory. Erase programmable read-only memory (Electrically EPROM, EEPROM) or flash memory.
- Volatile memory can be random access memory (Random Access Memory, RAM), static random access memory (Static RAM, SRAM), dynamic random access memory (Dynamic RAM, DRAM), synchronous dynamic random access memory (Synchronous DRAM, SDRAM), double data rate synchronous dynamic random access memory (Double Data Rate SDRAM, DDRSDRAM), enhanced synchronous dynamic random access memory (Enhanced SDRAM, ESDRAM), synchronous link dynamic random access memory (Synch link DRAM) , SLDRAM) and direct memory bus random access memory (Direct Rambus RAM, DRRAM).
- RAM Random Access Memory
- SRAM static random access memory
- DRAM dynamic random access memory
- DRAM synchronous dynamic random access memory
- SDRAM double data rate synchronous dynamic random access memory
- Double Data Rate SDRAM Double Data Rate SDRAM
- DDRSDRAM double data rate synchronous dynamic random access memory
- Enhanced SDRAM, ESDRAM enhanced synchronous dynamic random access memory
- Synch link DRAM synchronous link dynamic random access memory
- SLDRAM direct memory bus
- the processor 710 may include one or more processing units; optionally, the processor 710 integrates an application processor and a modem processor, where the application processor mainly handles operations related to the operating system, user interface, application programs, etc., Modem processors mainly process wireless communication signals, such as baseband processors. It can be understood that the above-mentioned modem processor may not be integrated into the processor 710.
- the processor 710 is used to obtain the first channel characteristic information, which is obtained by processing the first channel information by the network side device using the first model; according to the first channel characteristic information and the first channel characteristic information,
- the second channel information corresponding to the channel characteristic information matches the second model in the terminal 700 with the first model; the first channel information is the same as the second channel information; the first model is the same as the second channel information.
- the second model is a model trained in different devices; the second model is used to process channel information.
- the terminal 700 provided by the embodiment of the present application can implement each process implemented by the terminal in the method embodiment of Figure 4 and achieve the same technical effect. To avoid duplication, details will not be described here.
- the embodiment of the present application also provides a network side device.
- the network side device 80 includes: a processor 81 , a network interface 82 and a memory 83 .
- the network interface 82 is, for example, a common public radio interface (CPRI).
- CPRI common public radio interface
- the network side device 80 in this embodiment of the present invention also includes: instructions or programs stored in the memory 83 and executable on the processor 81.
- the processor 81 calls the instructions or programs in the memory 83 to execute what is shown in Figure 5 To avoid duplication, the methods for executing each module and achieving the same technical effect will not be described in detail here.
- Embodiments of the present application also provide a readable storage medium.
- Programs or instructions are stored on the readable storage medium.
- the program or instructions are executed by a processor, each process of the above model matching method embodiment is implemented, and the same can be achieved. The technical effects will not be repeated here to avoid repetition.
- the processor is the processor in the terminal described in the above embodiment.
- the readable storage medium includes computer readable storage media, such as computer read-only memory ROM, random access memory RAM, magnetic disk or optical disk, etc.
- An embodiment of the present application further provides a chip.
- the chip includes a processor and a communication interface.
- the communication interface is coupled to the processor.
- the processor is used to run programs or instructions to implement the above model matching method embodiment. Each process can achieve the same technical effect. To avoid duplication, it will not be described again here.
- chips mentioned in the embodiments of this application may also be called system-on-chip, system-on-a-chip, system-on-chip or system-on-chip, etc.
- Embodiments of the present application further provide a computer program/program product.
- the computer program/program product is stored in a storage medium.
- the computer program/program product is executed by at least one processor to implement the above model matching method embodiment.
- Each process can achieve the same technical effect. To avoid repetition, we will not go into details here.
- An embodiment of the present application also provides a communication system, including: a first device and a second device.
- the first device can be used to perform the steps of the model matching method as described above.
- the second device can utilize the first model. Process the first channel information to obtain first channel characteristic information, and send the first channel characteristic information to the first device.
- the methods of the above embodiments can be implemented by means of software plus the necessary general hardware platform. Of course, it can also be implemented by hardware, but in many cases the former is better. implementation.
- the technical solution of the present application can be embodied in the form of a computer software product that is essentially or contributes to the existing technology.
- the computer software product is stored in a storage medium (such as ROM/RAM, disk , CD), including several instructions to cause a terminal (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in various embodiments of this application.
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- General Health & Medical Sciences (AREA)
- Computing Systems (AREA)
- Biomedical Technology (AREA)
- Biophysics (AREA)
- Computational Linguistics (AREA)
- Data Mining & Analysis (AREA)
- Evolutionary Computation (AREA)
- Life Sciences & Earth Sciences (AREA)
- Molecular Biology (AREA)
- Artificial Intelligence (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Mathematical Physics (AREA)
- Software Systems (AREA)
- Health & Medical Sciences (AREA)
- Electromagnetism (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Mobile Radio Communication Systems (AREA)
Abstract
The present application relates to the technical field of communications, and discloses a model matching method and apparatus, a communication device, and a readable storage medium. The model matching method of embodiments of the present application comprises: a first device acquiring first channel feature information, the first channel feature information being obtained by a second device processing first channel information by means of a first model; and matching a second model of the first device with the first model according to the first channel feature information and second channel information corresponding to the first channel feature information, the first model and the second model being models obtained by training in different devices. When the first device is a network side device and the second device is a terminal, the second model is used for processing channel feature information acquired by the first device; or when the first device is a terminal and the second device is a network side device, the second model is used for processing channel information.
Description
相关申请的交叉引用Cross-references to related applications
本申请主张在2022年8月4日在中国提交的中国专利申请No.202210934857.5的优先权,其全部内容通过引用包含于此。This application claims priority from Chinese Patent Application No. 202210934857.5 filed in China on August 4, 2022, the entire content of which is incorporated herein by reference.
本申请属于通信技术领域,具体涉及一种模型匹配方法、装置、通信设备及可读存储介质。This application belongs to the field of communication technology, and specifically relates to a model matching method, device, communication equipment and readable storage medium.
目前,基于模型的信道信息反馈包括终端侧的编码部分和基站侧的解码部分,通常编码部分和解码部分是联合训练的,彼此匹配。但出于保密性的考虑和/或模型传递开销的考虑,基站和终端需要独立训练各自所需的模型。这种情况下,将会造成终端侧的编码模型和基站侧的解码模型无法匹配,终端侧的编码模型的输出无法通过基站侧的解码模型进行恢复,影响信道信息反馈。Currently, model-based channel information feedback includes a coding part on the terminal side and a decoding part on the base station side. Usually the coding part and the decoding part are jointly trained and match each other. However, due to confidentiality considerations and/or model transmission overhead, the base station and the terminal need to independently train their respective required models. In this case, the coding model on the terminal side and the decoding model on the base station side will not match, and the output of the coding model on the terminal side cannot be restored through the decoding model on the base station side, affecting channel information feedback.
发明内容Contents of the invention
本申请实施例提供一种模型匹配方法、装置、通信设备及可读存储介质,能够解决相关技术中终端侧和网络侧的模型无法匹配的问题。Embodiments of the present application provide a model matching method, device, communication equipment and readable storage medium, which can solve the problem in related technologies that the models on the terminal side and the network side cannot be matched.
第一方面,提供了一种模型匹配方法,包括:The first aspect provides a model matching method, including:
第一设备获取第一信道特征信息,所述第一信道特征信息是第二设备利用第一模型对第一信道信息进行处理得到;The first device acquires first channel characteristic information, which is obtained by the second device using the first model to process the first channel information;
所述第一设备根据所述第一信道特征信息以及与所述第一信道特征信息对应的第二信道信息,对所述第一设备的第二模型与所述第一模型进行匹配;The first device matches the second model of the first device with the first model according to the first channel characteristic information and the second channel information corresponding to the first channel characteristic information;
其中,所述第一信道信息与所述第二信道信息相同;所述第一模型和所述第二模型是在不同设备中训练得到的模型;当所述第一设备为网络侧设备,所述第二设备为终端时,所述第二模型用于对所述第一设备获取的信道特征信息进行处理;或者,当所述第一设备为终端,所述第二设备为网络侧设备时,所述第二模型用于对信道信息进行处理。Wherein, the first channel information is the same as the second channel information; the first model and the second model are models trained in different devices; when the first device is a network side device, the When the second device is a terminal, the second model is used to process the channel characteristic information obtained by the first device; or when the first device is a terminal and the second device is a network side device , the second model is used to process channel information.
第二方面,提供了一种模型匹配装置,包括:In the second aspect, a model matching device is provided, including:
获取模块,用于获取第一信道特征信息,所述第一信道特征信息是第二设备利用第一模型对第一信道信息进行处理得到;An acquisition module, configured to acquire first channel characteristic information, which is obtained by processing the first channel information by the second device using the first model;
匹配模块,用于根据所述第一信道特征信息以及与所述第一信道特征信息对应的第二信道信息,对所述第一设备的第二模型与所述第一模型进行匹配;A matching module configured to match the second model of the first device with the first model according to the first channel characteristic information and the second channel information corresponding to the first channel characteristic information;
其中,所述第一信道信息与所述第二信道信息相同;所述第一模型和所述第二模型是
在不同设备中训练得到的模型;当所述第一设备为网络侧设备,所述第二设备为终端时,所述第二模型用于对所述第一设备获取的信道特征信息进行处理;或者,当所述第一设备为终端,所述第二设备为网络侧设备时,所述第二模型用于对信道信息进行处理。Wherein, the first channel information and the second channel information are the same; the first model and the second model are Models trained in different devices; when the first device is a network-side device and the second device is a terminal, the second model is used to process the channel characteristic information obtained by the first device; Or, when the first device is a terminal and the second device is a network-side device, the second model is used to process channel information.
第三方面,提供了一种通信设备,该通信设备包括处理器和存储器,所述存储器存储可在所述处理器上运行的程序或指令,所述程序或指令被所述处理器执行时实现如第一方面所述的方法的步骤。In a third aspect, a communication device is provided. The communication device includes a processor and a memory. The memory stores a program or instructions that can be run on the processor. The program or instructions are implemented when executed by the processor. The steps of the method as described in the first aspect.
第四方面,提供了一种通信设备,该通信设备为第一设备,包括处理器及通信接口,所述处理器用于获取第一信道特征信息,所述第一信道特征信息是第二设备利用第一模型对第一信道信息进行处理得到;根据所述第一信道特征信息以及与所述第一信道特征信息对应的第二信道信息,对所述第一设备的第二模型与所述第一模型进行匹配;所述第一信道信息与所述第二信道信息相同;所述第一模型和所述第二模型是在不同设备中训练得到的模型;当所述第一设备为网络侧设备,所述第二设备为终端时,所述第二模型用于对所述第一设备获取的信道特征信息进行处理;或者,当所述第一设备为终端,所述第二设备为网络侧设备时,所述第二模型用于对信道信息进行处理。In a fourth aspect, a communication device is provided. The communication device is a first device and includes a processor and a communication interface. The processor is used to obtain first channel characteristic information. The first channel characteristic information is used by the second device. The first model is obtained by processing the first channel information; according to the first channel characteristic information and the second channel information corresponding to the first channel characteristic information, the second model of the first device and the third A model is used for matching; the first channel information is the same as the second channel information; the first model and the second model are models trained in different devices; when the first device is a network side device, when the second device is a terminal, the second model is used to process the channel characteristic information obtained by the first device; or, when the first device is a terminal, the second device is a network When a side device is used, the second model is used to process channel information.
第五方面,提供了一种通信***,包括:第一设备及第二设备,所述第一设备可用于执行如第一方面所述的模型匹配方法的步骤,所述第二设备可利用第一模型对第一信道信息进行处理,得到第一信道特征信息,并发送所述第一信道特征信息至第一设备。In a fifth aspect, a communication system is provided, including: a first device and a second device. The first device can be used to perform the steps of the model matching method as described in the first aspect. The second device can utilize the second device. A model processes the first channel information, obtains first channel characteristic information, and sends the first channel characteristic information to the first device.
第六方面,提供了一种可读存储介质,所述可读存储介质上存储程序或指令,所述程序或指令被处理器执行时实现如第一方面所述的方法的步骤。In a sixth aspect, a readable storage medium is provided. Programs or instructions are stored on the readable storage medium. When the programs or instructions are executed by a processor, the steps of the method described in the first aspect are implemented.
第七方面,提供了一种芯片,所述芯片包括处理器和通信接口,所述通信接口和所述处理器耦合,所述处理器用于运行程序或指令,实现如第一方面所述的方法的步骤。In a seventh aspect, a chip is provided. The chip includes a processor and a communication interface. The communication interface is coupled to the processor. The processor is used to run programs or instructions to implement the method described in the first aspect. A step of.
第八方面,提供了一种计算机程序/程序产品,所述计算机程序/程序产品被存储在存储介质中,所述计算机程序/程序产品被至少一个处理器执行以实现如第一方面所述的方法的步骤。In an eighth aspect, a computer program/program product is provided, the computer program/program product is stored in a storage medium, and the computer program/program product is executed by at least one processor to implement the method described in the first aspect Method steps.
在本申请实施例中,通过获取第一信道特征信息,所述第一信道特征信息是第二设备利用第一模型对第一信道信息进行处理得到,并根据第一信道特征信息以及与第一信道特征信息对应的第二信道信息,对第一设备的第二模型与第一模型进行匹配,可以使得分开独立训练的第一模型和第二模型匹配,从而使得终端侧模型所处理得到的信道特征信息,能够通过网络侧模型恢复得到相应的信道信息,从而保证信道信息反馈。In the embodiment of the present application, the first channel characteristic information is obtained by the second device using the first model to process the first channel information, and the first channel characteristic information is obtained according to the first channel characteristic information and the first channel characteristic information. The second channel information corresponding to the channel characteristic information matches the second model of the first device with the first model, so that the first model and the second model that are independently trained can be matched, so that the channel processed by the terminal side model Characteristic information can be recovered through the network side model to obtain corresponding channel information, thereby ensuring channel information feedback.
图1是本申请实施例可应用的一种无线通信***的框图;Figure 1 is a block diagram of a wireless communication system applicable to the embodiment of the present application;
图2是本申请实施例中的神经网络的示意图;Figure 2 is a schematic diagram of a neural network in an embodiment of the present application;
图3是本申请实施例中的神经元的示意图;Figure 3 is a schematic diagram of neurons in the embodiment of the present application;
图4是本申请实施例提供的一种模型匹配方法的流程图;
Figure 4 is a flow chart of a model matching method provided by an embodiment of the present application;
图5是本申请实施例提供的一种模型匹配装置的结构示意图;Figure 5 is a schematic structural diagram of a model matching device provided by an embodiment of the present application;
图6是本申请实施例提供的一种通信设备的结构示意图;Figure 6 is a schematic structural diagram of a communication device provided by an embodiment of the present application;
图7是本申请实施例提供的一种终端的结构示意图;Figure 7 is a schematic structural diagram of a terminal provided by an embodiment of the present application;
图8是本申请实施例提供的一种网络侧设备的结构示意图。Figure 8 is a schematic structural diagram of a network side device provided by an embodiment of the present application.
下面将结合本申请实施例中的附图,对本申请实施例中的技术方案进行清楚描述,显然,所描述的实施例是本申请一部分实施例,而不是全部的实施例。基于本申请中的实施例,本领域普通技术人员所获得的所有其他实施例,都属于本申请保护的范围。The technical solutions in the embodiments of the present application will be clearly described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, but not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art fall within the scope of protection of this application.
本申请的说明书和权利要求书中的术语“第一”、“第二”等是用于区别类似的对象,而不用于描述特定的顺序或先后次序。应该理解这样使用的术语在适当情况下可以互换,以便本申请的实施例能够以除了在这里图示或描述的那些以外的顺序实施,且“第一”、“第二”所区别的对象通常为一类,并不限定对象的个数,例如第一对象可以是一个,也可以是多个。此外,说明书以及权利要求中“和/或”表示所连接对象的至少其中之一,字符“/”一般表示前后关联对象是一种“或”的关系。The terms "first", "second", etc. in the description and claims of this application are used to distinguish similar objects and are not used to describe a specific order or sequence. It is to be understood that the terms so used are interchangeable under appropriate circumstances so that the embodiments of the present application can be practiced in sequences other than those illustrated or described herein, and that "first" and "second" are distinguished objects It is usually one type, and the number of objects is not limited. For example, the first object can be one or multiple. In addition, "and/or" in the description and claims indicates at least one of the connected objects, and the character "/" generally indicates that the related objects are in an "or" relationship.
值得指出的是,本申请实施例所描述的技术不限于长期演进型(Long Term Evolution,LTE)/LTE的演进(LTE-Advanced,LTE-A)***,还可用于其他无线通信***,诸如码分多址(Code Division Multiple Access,CDMA)、时分多址(Time Division Multiple Access,TDMA)、频分多址(Frequency Division Multiple Access,FDMA)、正交频分多址(Orthogonal Frequency Division Multiple Access,OFDMA)、单载波频分多址(Single-carrier Frequency Division Multiple Access,SC-FDMA)和其他***。本申请实施例中的术语“***”和“网络”常被可互换地使用,所描述的技术既可用于以上提及的***和无线电技术,也可用于其他***和无线电技术。以下描述出于示例目的描述了新空口(New Radio,NR)***,并且在以下大部分描述中使用NR术语,但是这些技术也可应用于NR***应用以外的应用,如第6代(6th Generation,6G)通信***。It is worth pointing out that the technology described in the embodiments of this application is not limited to Long Term Evolution (LTE)/LTE Evolution (LTE-Advanced, LTE-A) systems, and can also be used in other wireless communication systems, such as code Code Division Multiple Access (CDMA), Time Division Multiple Access (TDMA), Frequency Division Multiple Access (FDMA), Orthogonal Frequency Division Multiple Access, OFDMA), Single-carrier Frequency Division Multiple Access (SC-FDMA) and other systems. The terms "system" and "network" in the embodiments of this application are often used interchangeably, and the described technology can be used not only for the above-mentioned systems and radio technologies, but also for other systems and radio technologies. The following description describes a New Radio (NR) system for example purposes, and NR terminology is used in much of the following description, but these techniques can also be applied to applications other than NR system applications, such as 6th generation Generation, 6G) communication system.
图1示出本申请实施例可应用的一种无线通信***的框图。无线通信***包括终端11和网络侧设备12。其中,终端11可以是手机、平板电脑(Tablet Personal Computer)、膝上型电脑(Laptop Computer)或称为笔记本电脑、个人数字助理(Personal Digital Assistant,PDA)、掌上电脑、上网本、超级移动个人计算机(ultra-mobile personal computer,UMPC)、移动上网装置(Mobile Internet Device,MID)、增强现实(augmented reality,AR)/虚拟现实(virtual reality,VR)设备、机器人、可穿戴式设备(Wearable Device)、车载设备(Vehicle User Equipment,VUE)、行人终端(Pedestrian User Equipment,PUE)、智能家居(具有无线通信功能的家居设备,如冰箱、电视、洗衣机或者家具等)、游戏机、个人计算机(personal computer,PC)、柜员机或者自助机等终端侧设备,可穿戴式设备包括:智能手表、智能手环、智能耳机、智能眼镜、智能首饰(智能手镯、智能手链、智能戒指、智能
项链、智能脚镯、智能脚链等)、智能腕带、智能服装等。需要说明的是,在本申请实施例并不限定终端11的具体类型。网络侧设备12可以包括接入网设备或核心网设备,其中,接入网设备也可以称为无线接入网设备、无线接入网(Radio Access Network,RAN)、无线接入网功能或无线接入网单元。接入网设备可以包括基站、无线局域网(Wireless Local Area Network,WLAN)接入点或WiFi节点等,基站可被称为节点B、演进节点B(Evolved Node B,eNB)、接入点、基收发机站(Base Transceiver Station,BTS)、无线电基站、无线电收发机、基本服务集(Basic Service Set,BSS)、扩展服务集(Extended Service Set,ESS)、家用B节点、家用演进型B节点、发送接收点(Transmitting Receiving Point,TRP)或所述领域中其他某个合适的术语,只要达到相同的技术效果,所述基站不限于特定技术词汇,需要说明的是,在本申请实施例中仅以NR***中的基站为例进行介绍,并不限定基站的具体类型。核心网设备可以包含但不限于如下至少一项:核心网节点、核心网功能、移动管理实体(Mobility Management Entity,MME)、接入移动管理功能(Access and Mobility Management Function,AMF)、会话管理功能(Session Management Function,SMF)、用户平面功能(User Plane Function,UPF)、策略控制功能(Policy Control Function,PCF)、策略与计费规则功能单元(Policy and Charging Rules Function,PCRF)、边缘应用服务发现功能(Edge Application Server Discovery Function,EASDF)、统一数据管理(Unified Data Management,UDM),统一数据仓储(Unified Data Repository,UDR)、归属用户服务器(Home Subscriber Server,HSS)、集中式网络配置(Centralized network configuration,CNC)、网络存储功能(Network Repository Function,NRF),网络开放功能(Network Exposure Function,NEF)、本地NEF(Local NEF,或L-NEF)、绑定支持功能(Binding Support Function,BSF)、应用功能(Application Function,AF)等。需要说明的是,在本申请实施例中仅以NR***中的核心网设备为例进行介绍,并不限定核心网设备的具体类型。Figure 1 shows a block diagram of a wireless communication system to which embodiments of the present application are applicable. The wireless communication system includes a terminal 11 and a network side device 12. The terminal 11 may be a mobile phone, a tablet computer (Tablet Personal Computer), a laptop computer (Laptop Computer), or a notebook computer, a personal digital assistant (Personal Digital Assistant, PDA), a palmtop computer, a netbook, or a super mobile personal computer. (ultra-mobile personal computer, UMPC), mobile Internet device (Mobile Internet Device, MID), augmented reality (AR)/virtual reality (VR) equipment, robots, wearable devices (Wearable Device) , Vehicle User Equipment (VUE), Pedestrian User Equipment (PUE), smart home (home equipment with wireless communication functions, such as refrigerators, TVs, washing machines or furniture, etc.), game consoles, personal computers (personal computer, PC), teller machine or self-service machine and other terminal-side equipment. Wearable devices include: smart watches, smart bracelets, smart headphones, smart glasses, smart jewelry (smart bracelets, smart bracelets, smart rings, smart Necklaces, smart anklets, smart anklets, etc.), smart wristbands, smart clothing, etc. It should be noted that the embodiment of the present application does not limit the specific type of the terminal 11. The network side device 12 may include an access network device or a core network device, where the access network device may also be called a radio access network device, a radio access network (Radio Access Network, RAN), a radio access network function or a wireless access network unit. Access network equipment may include a base station, a Wireless Local Area Network (WLAN) access point or a WiFi node, etc. The base station may be called a Node B, an Evolved Node B (eNB), an access point, or a base station. Base Transceiver Station (BTS), radio base station, radio transceiver, Basic Service Set (BSS), Extended Service Set (ESS), home B-node, home evolved B-node, Transmitting Receiving Point (TRP) or some other appropriate term in the field, as long as the same technical effect is achieved, the base station is not limited to specific technical terms. It should be noted that in the embodiment of this application, only The base station in the NR system is taken as an example for introduction, and the specific type of base station is not limited. Core network equipment may include but is not limited to at least one of the following: core network nodes, core network functions, mobility management entities (Mobility Management Entity, MME), access mobility management functions (Access and Mobility Management Function, AMF), session management functions (Session Management Function, SMF), User Plane Function (UPF), Policy Control Function (PCF), Policy and Charging Rules Function (PCRF), Edge Application Service Discovery function (Edge Application Server Discovery Function, EASDF), Unified Data Management (UDM), Unified Data Repository (UDR), Home Subscriber Server (HSS), centralized network configuration ( Centralized network configuration (CNC), Network Repository Function (NRF), Network Exposure Function (NEF), Local NEF (Local NEF, or L-NEF), Binding Support Function (Binding Support Function, BSF), application function (Application Function, AF), etc. It should be noted that in the embodiment of this application, only the core network equipment in the NR system is used as an example for introduction, and the specific type of the core network equipment is not limited.
可选的,本申请实施例中的模型可以为人工智能(Artificial Intelligence,AI)模型。AI模型有多种算法实现方式,例如神经网络、决策树、支持向量机、贝叶斯分类器等。本申请以神经网络为例进行说明,但是并不限定AI模块的具体类型。Optionally, the model in the embodiment of this application may be an artificial intelligence (Artificial Intelligence, AI) model. AI models have a variety of algorithm implementations, such as neural networks, decision trees, support vector machines, Bayesian classifiers, etc. This application takes neural network as an example for explanation, but does not limit the specific type of AI module.
例如,一个神经网络的示意图可以如图2所示,其中,X1、X2…Xn等为输入值,Y为输出结果,一个个“○”代表一个个神经元即是进行运算的地方,结果会继续传入到下一层。这些众多神经元组成的输入层、隐藏层和输出层就是一个神经网络。隐藏层的数量以及每一层神经元的数量即是神经网络的“网络结构”。For example, the schematic diagram of a neural network can be shown in Figure 2, in which X 1 , The results will continue to be passed to the next layer. The input layer, hidden layer and output layer composed of these many neurons is a neural network. The number of hidden layers and the number of neurons in each layer is the "network structure" of the neural network.
又例如,神经网络由神经元组成,神经元的示意图可以如图3所示,其中,a1、ak…aK(即图2所示的X1、X2…)为输入,w为权值(也可称为:乘性系数),b为偏置(也可称为:加性系数),σ()为激活函数,z为输出值,相应运算过程可表示为:
常见的激活函数包括但不限于Sigmoid函数、双曲正切tanh函数、修正线性单元(Rectified Linear Unit,ReLU)等等。每一个神经元的参数信息和所用算法组合在一起就是整个神经网络的“参数信息”,也是AI模型文件中很重要的一部分。
For another example, a neural network is composed of neurons, and the schematic diagram of the neurons can be shown in Figure 3, where a 1 , a k ...a K (i.e., X1, X2... shown in Figure 2) are inputs, and w is the weight. (can also be called: multiplicative coefficient), b is the bias (can also be called: additive coefficient), σ() is the activation function, z is the output value, and the corresponding operation process can be expressed as: Common activation functions include but are not limited to Sigmoid function, hyperbolic tanh function, rectified linear unit (Rectified Linear Unit, ReLU), etc. The parameter information of each neuron and the algorithm used are combined to form the "parameter information" of the entire neural network, which is also an important part of the AI model file.
神经网络的参数可以通过优化算法进行优化。优化算法是一种能够最小化或者最大化目标函数(有时候也叫损失函数)的一类算法。目标函数往往是模型参数和数据的数学组合。例如,给定数据x和其对应的标签Y,并构建一个神经网络模型f(.),有了模型后,根据输入数据x可以得到预测输出f(x),并且可以计算出预测值和真实值之间的差距(f(x)-Y),这个就是损失函数。此时的目的是,找到合适的模型参数(比如:权值/偏置)使上述的损失函数的值达到最小,损失值越小,则说明模型越接近于真实情况。The parameters of neural networks can be optimized through optimization algorithms. An optimization algorithm is a type of algorithm that can minimize or maximize an objective function (sometimes also called a loss function). The objective function is often a mathematical combination of model parameters and data. For example, given data x and its corresponding label Y, and constructing a neural network model f(.), with the model, the predicted output f(x) can be obtained based on the input data x, and the predicted value and the true value can be calculated The difference between the values (f(x)-Y), this is the loss function. The purpose at this time is to find appropriate model parameters (such as weights/biases) to minimize the value of the above loss function. The smaller the loss value, the closer the model is to the real situation.
可选的,优化算法包含误差反向传播(error Back Propagation,BP)算法。BP算法的基本思想是,学习过程由信号的正向传播与误差的反向传播两个过程组成。正向传播时,输入样本从输入层传入,经各隐藏层逐层处理后,传向输出层。若输出层的实际输出与期望的输出不符,则转入误差的反向传播阶段。误差的反向传播是将输出误差以某种形式通过隐藏层向输入层逐层反传,并将误差分摊给各层的所有单元,从而获得各层单元的误差信号,此误差信号即作为修正各单元的权值的依据。这种信号正向传播与误差反向传播的各层权值调整过程,是周而复始地进行的。权值不断调整的过程,也就是神经网络的学习训练过程。此过程一直进行到网络输出的误差减少到可接受的程度,或进行到预先设定的学习次数为止。Optionally, the optimization algorithm includes error back propagation (error Back Propagation, BP) algorithm. The basic idea of BP algorithm is that the learning process consists of two processes: forward propagation of signals and back propagation of errors. During forward propagation, the input sample is passed in from the input layer, processed layer by layer by each hidden layer, and then transmitted to the output layer. If the actual output of the output layer does not match the expected output, it will enter the error backpropagation stage. The back propagation of error is to back propagate the output error in some form to the input layer layer by layer through the hidden layer, and allocate the error to all units in each layer, thereby obtaining the error signal of each layer unit, and this error signal is used as a correction The basis for the weight of each unit. This process of adjusting the weights of each layer in forward signal propagation and error back propagation is carried out over and over again. The process of continuous adjustment of weights is the learning and training process of the neural network. This process continues until the error of the network output is reduced to an acceptable level, or until a preset number of learning times.
可选的,优化算法可以包括但不限于:梯度下降(Gradient Descent)、随机梯度下降(Stochastic Gradient Descent,SGD)、小批量梯度下降(mini-batch gradient descent)、动量法(Momentum)、带动量的随机梯度下降(如Nesterov)、自适应梯度下降(ADAptive GRADient descent,Adagrad)、Adadelta算法、均方根误差降速(root mean square prop,RMSprop)、自适应动量估计(Adaptive Moment Estimation,Adam)等。这些优化算法在误差反向传播时,可以根据损失函数得到的误差/损失,对当前神经元求取导数/偏导,加上学习速率、之前的梯度/导数/偏导等影响,得到梯度,并将梯度传给上一层。Optional, optimization algorithms may include but are not limited to: gradient descent (Gradient Descent), stochastic gradient descent (Stochastic Gradient Descent, SGD), mini-batch gradient descent (mini-batch gradient descent), momentum method (Momentum), driven momentum Stochastic gradient descent (such as Nesterov), adaptive gradient descent (ADAptive GRADient descent, Adagrad), Adadelta algorithm, root mean square error reduction (root mean square prop, RMSprop), adaptive momentum estimation (Adaptive Moment Estimation, Adam) wait. When these optimization algorithms perform error backpropagation, they can calculate the derivative/partial derivative of the current neuron based on the error/loss obtained by the loss function, plus the influence of the learning rate, previous gradient/derivative/partial derivative, etc., to obtain the gradient. And pass the gradient to the previous layer.
本申请实施例中,编码网络(或称为编码模型)的作用是将信道信息压缩为信道特征信息,解码网络(或称为解码模型)作用是将信道特征信息恢复为相应的信道信息,因此编码网络的压缩方式和解码网络的恢复方式需要相互匹配。但由于性能好的模型往往模型大小比较大,传递开销很大,而且基站和终端可能不希望对方获知自己使用的模型以及进行的优化处理,因此基站和终端可独立训练所需的模型。这时需要额外的模型匹配过程,以使分开独立训练的编码模型和解码模型匹配,使得终端侧编码模型所编码得到的信道特征信息,能够通过网络侧编码模型解码得到相应的信道信息,从而保证信道信息反馈。In the embodiment of this application, the function of the encoding network (or coding model) is to compress channel information into channel characteristic information, and the function of the decoding network (or called decoding model) is to restore the channel characteristic information into corresponding channel information. Therefore The compression method of the encoding network and the recovery method of the decoding network need to match each other. However, since models with good performance often have relatively large model sizes and high transmission overhead, and the base station and the terminal may not want the other party to know the model they use and the optimization processing, the base station and the terminal can independently train the required model. At this time, an additional model matching process is required to match the independently trained encoding model and decoding model, so that the channel characteristic information encoded by the terminal-side encoding model can be decoded by the network-side encoding model to obtain the corresponding channel information, thereby ensuring Channel information feedback.
下面结合附图,通过一些实施例及其应用场景对本申请实施例提供的模型匹配方法、装置、通信设备及可读存储介质进行详细地说明。The model matching method, device, communication device and readable storage medium provided by the embodiments of the present application will be described in detail through some embodiments and application scenarios with reference to the accompanying drawings.
请参见图4,图4是本申请实施例提供的一种模型匹配方法的流程图,该方法应用于第一设备,所述第一设备可选为终端或者网络侧设备,所述网络侧设备比如为基站或核心网设备。如图4所示,该方法包括如下步骤:Please refer to Figure 4. Figure 4 is a flow chart of a model matching method provided by an embodiment of the present application. The method is applied to a first device. The first device can be a terminal or a network side device. The network side device For example, it is a base station or core network equipment. As shown in Figure 4, the method includes the following steps:
步骤41:第一设备获取第一信道特征信息,所述第一信道特征信息是第二设备利用
第一模型对第一信道信息进行处理得到。Step 41: The first device obtains the first channel characteristic information. The first channel characteristic information is used by the second device. The first model is obtained by processing the first channel information.
步骤42:第一设备根据第一信道特征信息以及与第一信道特征信息对应的第二信道信息,对第一设备的第二模型与第一模型进行匹配。Step 42: The first device matches the second model of the first device with the first model according to the first channel characteristic information and the second channel information corresponding to the first channel characteristic information.
本实施例中,上述的第一模型和第二模型是在不同设备中训练得到的模型。当第一设备为网络侧设备,第二设备为终端时,第二模型用于对第一设备(即网络侧设备,比如基站)获取的信道特征信息进行处理;或者,当第一设备为终端,第二设备为网络侧设备时,第二模型用于对信道信息进行处理。优先的,上述的第一信道信息与第二信道信息相同,也就是说,第一信道信息与第二信道信息是分别位于第二设备和第一设备的相同的信道信息,一个为用于第一模型对第一信道信息进行处理,另一个为用于模型匹配。In this embodiment, the above-mentioned first model and second model are models trained on different devices. When the first device is a network-side device and the second device is a terminal, the second model is used to process the channel characteristic information obtained by the first device (i.e., network-side device, such as a base station); or, when the first device is a terminal , when the second device is a network-side device, the second model is used to process channel information. Preferably, the above-mentioned first channel information and the second channel information are the same, that is to say, the first channel information and the second channel information are the same channel information located in the second device and the first device respectively, and one is used for the first device. One model processes the first channel information, and the other is used for model matching.
可选的,上述的第一信道特征信息可以是第二设备利用第一模型对第一信道信息进行编码/压缩得到。此情况下,第一模型可理解为在第二设备中训练得到的编码模型。上述对第一设备获取的信道特征信息进行处理可理解为,对该信道特征信息进行解码/解压缩。上述对信道信息进行处理可理解为,对该信道信息进行编码/压缩。Optionally, the above-mentioned first channel characteristic information may be obtained by the second device using the first model to encode/compress the first channel information. In this case, the first model can be understood as a coding model trained in the second device. The above processing of the channel characteristic information obtained by the first device can be understood as decoding/decompressing the channel characteristic information. The above processing of channel information can be understood as encoding/compressing the channel information.
一些实施例中,上述的第一信道信息/第二信道信息可选为但不限于信道矩阵、预编码矩阵等。In some embodiments, the above-mentioned first channel information/second channel information may be, but is not limited to, a channel matrix, a precoding matrix, etc.
比如,当第一设备为网络侧设备,第二设备为终端时,第一模型为终端中训练得到的用于对信道信息进行编码的编码模型,第二模型为网络侧设备中训练得到的用于对获取的信道特征信息进行解码的解码模型。这样,借助对第二模型与第一模型进行匹配,比如信道信息在终端第一模型的编码结果作为网络侧解码模型的输入,而这个信道信息作为解码模型的输出,对解码模型进行训练,可以使得分开独立训练的编码模型和解码模型匹配,从而使得终端侧编码模型所编码得到的信道特征信息,能够通过网络侧编码模型解码得到相应的信道信息,从而保证信道信息反馈。For example, when the first device is a network-side device and the second device is a terminal, the first model is a coding model trained in the terminal for encoding channel information, and the second model is a coding model trained in the network-side device. A decoding model used to decode the acquired channel characteristic information. In this way, by matching the second model with the first model, for example, the encoding result of the channel information in the first model of the terminal is used as the input of the network-side decoding model, and this channel information is used as the output of the decoding model, and the decoding model can be trained. The encoding model and the decoding model trained separately are matched, so that the channel characteristic information encoded by the terminal-side encoding model can be decoded by the network-side encoding model to obtain the corresponding channel information, thereby ensuring channel information feedback.
又比如,当第一设备为终端,第二设备为网络侧设备时,第一模型为网络侧设备中训练得到的用于对信道信息进行编码的编码模型,第二模型为终端中训练得到的用于对信道信息进行编码的编码模型。由于针对信道信息,网络侧设备训练的编码模型和解码模型是匹配的,终端训练的编码模型和解码模型是匹配的,因此,借助对第二模型与第一模型进行匹配,可以使得网络侧设备训练的编码模型与终端训练的编码模型匹配,从而使得终端侧编码模型所编码得到的信道特征信息,能够通过网络侧编码模型解码得到相应的信道信息,从而保证信道信息反馈。For another example, when the first device is a terminal and the second device is a network-side device, the first model is a coding model trained in the network-side device for encoding channel information, and the second model is a coding model trained in the terminal. Coding model used to encode channel information. Since the encoding model and decoding model trained by the network side device match the channel information, and the encoding model and decoding model trained by the terminal match, therefore, by matching the second model with the first model, the network side device can The trained coding model matches the coding model trained by the terminal, so that the channel characteristic information encoded by the terminal-side coding model can be decoded by the network-side coding model to obtain the corresponding channel information, thereby ensuring channel information feedback.
本申请实施例的模型匹配方法,通过获取第一信道特征信息,所述第一信道特征信息是第二设备利用第一模型对第一信道信息进行处理得到,并根据第一信道特征信息以及与第一信道特征信息对应的第二信道信息,对第一设备的第二模型与第一模型进行匹配,可以使得分开独立训练的第一模型和第二模型匹配,从而使得终端侧模型所处理得到的信道特征信息,能够通过网络侧模型恢复得到相应的信道信息,从而保证信道信息反馈。The model matching method in the embodiment of the present application obtains the first channel characteristic information, which is obtained by the second device using the first model to process the first channel information, and based on the first channel characteristic information and the The second channel information corresponding to the first channel characteristic information matches the second model of the first device with the first model, so that the first model and the second model that are independently trained can be matched, so that the terminal side model processes the The channel characteristic information can be recovered through the network side model to obtain the corresponding channel information, thereby ensuring channel information feedback.
进一步的,借助模型匹配过程,可以避免进行模型传输,从而节省开销,还可以满足
网络侧设备和终端的不希望对方获知自己使用的模型以及相应优化处理的需求。Furthermore, with the help of the model matching process, model transmission can be avoided, thereby saving overhead and meeting the requirements of Network-side devices and terminals do not want the other party to know the model they are using and the need for corresponding optimization processing.
可选的,上述对第一设备的第二模型与第一模型进行匹配之前,第一设备可以接收第二信道信息的标识,然后根据所述第二信道信息的标识,确定与第一信道特征信息对应的第二信道信息,以便根据第一信道特征信以及对应的第二信道信息进行模型匹配。比如,当第一设备是基站时,首先,基站发送指示信息,指示终端进行匹配信息上报的时间,或者周期等;然后,终端根据指示信息确定对应的时间或者根据指示的周期计算对应的时间,并在对应的时间内,在配置的时频资源上上报匹配信息,包括第一信道特征信息和对应的信道信息在第一数据集中的标识(Identity,ID),这个ID作为第二信道信息的标识;之后,基站接收到这个ID之后,在第一数据集中找到对应的第二信道信息。Optionally, before matching the second model of the first device with the first model, the first device may receive an identifier of the second channel information, and then determine the characteristics of the first channel based on the identifier of the second channel information. The second channel information corresponding to the information is used to perform model matching based on the first channel characteristic information and the corresponding second channel information. For example, when the first device is a base station, first, the base station sends indication information to instruct the terminal on the time, period, etc. to report matching information; then, the terminal determines the corresponding time based on the indication information or calculates the corresponding time based on the indicated period. And within the corresponding time, the matching information is reported on the configured time-frequency resources, including the first channel characteristic information and the identification (Identity, ID) of the corresponding channel information in the first data set. This ID is used as the second channel information. identification; then, after receiving the ID, the base station finds the corresponding second channel information in the first data set.
可选的,上述对第一设备的第二模型与第一模型进行匹配之前,第一设备可以根据获取的第一信道特征信息的时频域位置,确定与第一信道特征信息对应的第二信道信息,以便根据第一信道特征信以及对应的第二信道信息进行模型匹配。比如,终端可以在指定的时频域位置上发送信道特征信息,由基站根据该时频域位置确定该信道特征信息对应的信道信息。Optionally, before matching the second model of the first device with the first model, the first device may determine the second model corresponding to the first channel characteristic information based on the obtained time-frequency domain position of the first channel characteristic information. Channel information to perform model matching based on the first channel characteristic information and the corresponding second channel information. For example, the terminal can send channel characteristic information at a designated time-frequency domain position, and the base station determines channel information corresponding to the channel characteristic information based on the time-frequency domain position.
可选的,上述的时频域位置可以由网络侧配置。比如,基站为终端配置用于发送信道特征信息的时频域位置。Optionally, the above time-frequency domain position can be configured by the network side. For example, the base station configures the time-frequency domain location for the terminal to send channel characteristic information.
可选的,上述的第一信道信息和第二信道信息可以为第一数据集中的信道信息,所述第一数据集中的信道信息用于进行模型匹配。即,终端和网络侧设备可以根据相同的包含信道信息的第一数据集进行模型处理。所述第一数据集可称为匹配数据集。比如,终端根据匹配数据集中的信道信息生成对应的编码结果,即信道特征信息,终端将信道特征信息发送给基站,基站根据匹配数据集中的信道信息以及对应的信道特征信息,对终端的编码模型进行匹配。Optionally, the above-mentioned first channel information and second channel information may be channel information in a first data set, and the channel information in the first data set is used for model matching. That is, the terminal and the network side device can perform model processing based on the same first data set containing channel information. The first data set may be referred to as a matching data set. For example, the terminal generates the corresponding coding result, that is, channel characteristic information, based on the channel information in the matching data set. The terminal sends the channel characteristic information to the base station. The base station codes the terminal's coding model based on the channel information in the matching data set and the corresponding channel characteristic information. Make a match.
一些实施例中,终端可以使用数据集A训练信道状态信息(Channel State Information,CSI)压缩的AI模型,包括编码模型和解码模型,基站可以使用数据集B训练CSI压缩的AI模型,包括编码模型和解码模型。特别的,数据集A和数据集B可以相同,也可以不同。进一步的模型匹配过程使用的匹配数据集可以与数据集A和数据集B都不同。In some embodiments, the terminal can use data set A to train a channel state information (CSI) compressed AI model, including a coding model and a decoding model, and the base station can use data set B to train a CSI compressed AI model, including a coding model. and decoding models. In particular, data set A and data set B can be the same or different. The matching data set used by the further model matching process can be different from both data set A and data set B.
可选的,所述第一信道信息和第二信道信息在第一数据集包含的信道信息中的顺序可以由协议约定或者网络侧配置。比如由协议约定时,所述第一信道信息和第二信道信息在第一数据集包含的信道信息中的顺序是固定的。Optionally, the order of the first channel information and the second channel information in the channel information contained in the first data set may be agreed by the protocol or configured by the network side. For example, when agreed by a protocol, the order of the first channel information and the second channel information in the channel information contained in the first data set is fixed.
可选的,第一设备可以从第二设备接收第一数据集。比如,第一数据集可以是基站实时发送给终端的,终端对接收的第一数据集中的某信道信息进行编码,得到信道特征信息并反馈给基站,由基站基于该信道特征信息以及相应的信道信息进行模型匹配。又比如,第一数据集可以是终端实时测量的,终端将估计得到的信道信息和编码后的信道特征信息一起发送给基站,由基站基于该信道特征信息以及相应的信道信息进行模型匹配。Optionally, the first device may receive the first data set from the second device. For example, the first data set can be sent by the base station to the terminal in real time. The terminal encodes certain channel information in the received first data set to obtain the channel characteristic information and feeds it back to the base station. The base station then codes based on the channel characteristic information and the corresponding channel. information for model matching. For another example, the first data set may be measured by the terminal in real time. The terminal sends the estimated channel information and the encoded channel characteristic information to the base station, and the base station performs model matching based on the channel characteristic information and corresponding channel information.
可选的,上述的第一数据集可以满足以下至少一项:
Optionally, the above-mentioned first data set can satisfy at least one of the following:
由终端采集;Collected by terminal;
由网络侧设备采集;Collected by network side equipment;
由协议约定;stipulated by agreement;
由网络侧设备指示的第二数据集中的子集,所述第二数据集被划分为多个子集;比如,所述第二数据集可以由协议约定;A subset of the second data set indicated by the network side device, where the second data set is divided into multiple subsets; for example, the second data set may be agreed upon by a protocol;
由不同于第一设备和第二设备的第三设备提供,该第三设备可理解为独立设备、独立节点等。Provided by a third device different from the first device and the second device, the third device may be understood as an independent device, an independent node, etc.
可选的,当第一数据集为由网络侧设备指示的第二数据集中的子集时,当终端执行模型匹配时,终端可以接收网络侧设备的配置信息,所述配置信息用于配置第一数据集的标识;然后,根据所述第一数据集的标识,从第二数据集中选择第一数据集。比如,第二数据集的范围由协议约定,并划分为多个子集,由基站选择并指示终端使用的子集(即第一数据集)。Optionally, when the first data set is a subset of the second data set indicated by the network side device, when the terminal performs model matching, the terminal may receive configuration information of the network side device, where the configuration information is used to configure the third data set. An identifier of a data set; then, select the first data set from the second data set according to the identifier of the first data set. For example, the range of the second data set is agreed upon by the protocol and divided into multiple subsets, and the base station selects and instructs the terminal to use the subset (ie, the first data set).
可选的,所述第二数据集可以是协议约定的,或者是由不同于第一设备和第二设备的第三设备提供采集或更新的。所述第二数据集的采集和/或更新可以是离线的或长期的。网络侧设备比如基站可以在第二数据集中指示其中一部分为第一数据集,比如指示信息可以为下行控制信息(Downlink Control Information,DCI)、媒体接入控制控制单元(Medium Access Control Control Element,MAC CE)或者无线资源控制(Radio Resource Control,RRC)信令等。Optionally, the second data set may be agreed upon in a protocol, or may be collected or updated by a third device different from the first device and the second device. The collection and/or updating of the second data set may be offline or long-term. The network side equipment such as the base station can indicate in the second data set that part of it is the first data set. For example, the indication information can be downlink control information (Downlink Control Information, DCI), medium access control control element (Medium Access Control Control Element, MAC). CE) or Radio Resource Control (Radio Resource Control, RRC) signaling, etc.
可选的,当第一数据集由不同于第一设备和第二设备的第三设备提供时,在第一数据集更新后,第一设备可以执行以下任一项:与第二设备和/或第三设备交互更新后的第一数据集的版本,与第二设备和/或第三设备交互更新后的第一数据集;并利用更新后的第一数据集进行模型匹配。和/或,在第一数据集更新后,更新后的第一数据集和/或更新后的第一数据集的版本可以在第三设备与第二设备之间交互。也就是说,在第三设备更新第一数据集之后,第三设备可以通过与第一设备和/或第二设备的交互,告知第一设备和/或第二设备更新后的第一数据集,而第一设备和第二设备之间也可交互更新后的第一数据集。Optionally, when the first data set is provided by a third device different from the first device and the second device, after the first data set is updated, the first device may perform any of the following: communicate with the second device and/or Or the third device interacts with the updated version of the first data set, interacts with the second device and/or the third device with the updated first data set; and uses the updated first data set to perform model matching. And/or, after the first data set is updated, the updated first data set and/or the updated version of the first data set may be interacted between the third device and the second device. That is to say, after the third device updates the first data set, the third device can notify the first device and/or the second device of the updated first data set through interaction with the first device and/or the second device. , and the first device and the second device can also interact with the updated first data set.
一些实施例中,在第一数据集更新后,基站和终端可以通过信令交互更新后的第一数据集的版本,以使用相同版本的第一数据集进行模型匹配。In some embodiments, after the first data set is updated, the base station and the terminal may exchange the updated version of the first data set through signaling to use the same version of the first data set for model matching.
一些实施例中,当第一数据集由不同于第一设备和第二设备的第三设备提供时,第三设备可以定期更新第一数据集,并发送给第一设备和/或第二设备。特别的,第一数据集可以通过数据面发送。In some embodiments, when the first data set is provided by a third device different from the first device and the second device, the third device can periodically update the first data set and send it to the first device and/or the second device. . In particular, the first data set can be sent via the data plane.
可选的,当第二数据集由不同于第一设备和第二设备的第三设备提供时,在第二数据集更新后,第一设备可以执行以下任一项:与第二设备和/或第三设备交互更新后的第二数据集的版本,与第二设备和/或第三设备交互更新后的第二数据集。和/或,在第二数据集更新后,更新后的第二数据集和/或更新后的第二数据集的版本可以在第三设备与第二设备之间交互。也就是说,在第三设备更新第二数据集之后,第三设备可以通过与第一设
备和/或第二设备的交互,告知第一设备和/或第二设备更新后的第二数据集,而第一设备和第二设备之间也可交互更新后的第二数据集。Optionally, when the second data set is provided by a third device different from the first device and the second device, after the second data set is updated, the first device may perform any of the following: communicate with the second device and/or or the third device interacts with the updated version of the second data set, and interacts with the second device and/or the third device with the updated second data set. And/or, after the second data set is updated, the updated second data set and/or a version of the updated second data set may be interacted between the third device and the second device. That is to say, after the third device updates the second data set, the third device can communicate with the first device The first device and/or the second device may interact with each other to inform the first device and/or the second device of the updated second data set, and the first device and the second device may also interact with the updated second data set.
可选的,当第一设备为网络侧设备,第二设备为终端时,上述对第一设备的第二模型与第一模型进行匹配可以包括以下至少一项:Optionally, when the first device is a network-side device and the second device is a terminal, the above-mentioned matching of the second model of the first device with the first model may include at least one of the following:
第一设备将第一信道特征信息作为第二模型的输入,并将第二信道信息作为第二模型的输出,重新训练第二模型;The first device uses the first channel characteristic information as the input of the second model, uses the second channel information as the output of the second model, and retrains the second model;
第一设备根据第一信道特征信息以及第二信道信息,调整第二模型的参数。The first device adjusts the parameters of the second model according to the first channel characteristic information and the second channel information.
也就是说,当进行模型匹配时,在网络侧设备(如基站)侧,可以将第一模型(如编码模型/编码器)的输出作为第二模型(如解码模型/解码器)的输入来训练第二模型(如解码模型/解码器),和/或调整第二模型(如解码模型/解码器)的参数。此时所要实现的是:第一模型(如编码模型/编码器)的输入与第二模型(如解码模型/解码器)的输出为同一个信道信息。That is to say, when performing model matching, on the network side device (such as base station) side, the output of the first model (such as encoding model/encoder) can be used as the input of the second model (such as decoding model/decoder). Train a second model (eg, decoding model/decoder), and/or adjust parameters of the second model (eg, decoding model/decoder). What needs to be realized at this time is that the input of the first model (such as the encoding model/encoder) and the output of the second model (such as the decoding model/decoder) are the same channel information.
这样,借助重新训练第二模型和/或调整第二模型的参数,可以使得分开独立训练的第一模型和第二模型匹配,从而使得终端侧模型所处理得到的信道特征信息,能够通过网络侧模型恢复得到相应的信道信息,从而保证信道信息反馈。In this way, by retraining the second model and/or adjusting the parameters of the second model, the first model and the second model that are independently trained can be matched, so that the channel characteristic information processed by the terminal side model can be passed through the network side. The model is restored to obtain corresponding channel information, thereby ensuring channel information feedback.
可选的,当第一设备为终端,第二设备为网络侧设备时,上述对第一设备的第二模型与第一模型进行匹配可以包括以下至少一项:Optionally, when the first device is a terminal and the second device is a network-side device, the above-mentioned matching of the second model of the first device with the first model may include at least one of the following:
第一设备将第一信道特征信息作为第二模型的输出,并将第二信道信息作为第二模型的输入,重新训练第二模型;The first device uses the first channel characteristic information as the output of the second model, uses the second channel information as the input of the second model, and retrains the second model;
第一设备根据第一信道特征信息以及第二信道信息,调整第二模型的参数。The first device adjusts the parameters of the second model according to the first channel characteristic information and the second channel information.
也就是说,当进行模型匹配时,在终端侧,第一模型(如编码模型/编码器)和第二模型(如编码模型/编码器)的输入为相同的信道信息,可以通过训练第二模型(如编码模型/编码器)或者调整第二模型(如编码模型/编码器),使得这个第二模型(如编码模型/编码器)的输出结果和第一模型(如编码模型/编码器)的输出结果匹配,即相同。That is to say, when performing model matching, on the terminal side, the inputs of the first model (such as encoding model/encoder) and the second model (such as encoding model/encoder) are the same channel information, and the second model can be trained by model (such as encoding model/encoder) or adjust the second model (such as encoding model/encoder) so that the output result of this second model (such as encoding model/encoder) is consistent with the first model (such as encoding model/encoder) )'s output results match, that is, they are the same.
这样,借助重新训练第二模型和/或调整第二模型的参数,可以使得分开独立训练的第一模型和第二模型匹配,从而使得终端侧模型所处理得到的信道特征信息,能够通过网络侧模型恢复得到相应的信道信息,从而保证信道信息反馈。In this way, by retraining the second model and/or adjusting the parameters of the second model, the first model and the second model that are independently trained can be matched, so that the channel characteristic information processed by the terminal side model can be passed through the network side. The model is restored to obtain corresponding channel information, thereby ensuring channel information feedback.
本申请实施例提供的模型匹配方法,执行主体可以为模型匹配装置。本申请实施例中以模型匹配装置执行模型匹配方法为例,说明本申请实施例提供的模型匹配装置。For the model matching method provided by the embodiments of the present application, the execution subject may be a model matching device. In the embodiment of the present application, the model matching device executing the model matching method is used as an example to illustrate the model matching device provided by the embodiment of the present application.
请参见图5,图5是本申请实施例提供的一种模型匹配装置的结构示意图,该装置应用于第一设备,该第一设备可选为终端或者网络侧设备,该网络侧设备比如为基站或核心网设备。如图5所示,模型匹配装置50包括:Please refer to Figure 5. Figure 5 is a schematic structural diagram of a model matching device provided by an embodiment of the present application. The device is applied to a first device. The first device can be a terminal or a network side device. The network side device is, for example, Base station or core network equipment. As shown in Figure 5, the model matching device 50 includes:
获取模块51,用于获取第一信道特征信息,所述第一信道特征信息是第二设备利用第一模型对第一信道信息进行处理得到;The acquisition module 51 is used to obtain the first channel characteristic information, which is obtained by the second device using the first model to process the first channel information;
匹配模块52,用于根据所述第一信道特征信息以及与所述第一信道特征信息对应的
第二信道信息,对所述第一设备的第二模型与所述第一模型进行匹配;Matching module 52, configured to match the first channel characteristic information and the first channel characteristic information corresponding to the first channel characteristic information. second channel information, matching the second model of the first device with the first model;
其中,所述第一信道信息与所述第二信道信息相同;所述第一模型和所述第二模型是在不同设备中训练得到的模型;当所述第一设备为网络侧设备,所述第二设备为终端时,所述第二模型用于对所述第一设备获取的信道特征信息进行处理;或者,当所述第一设备为终端,所述第二设备为网络侧设备时,所述第二模型用于对信道信息进行处理。Wherein, the first channel information is the same as the second channel information; the first model and the second model are models trained in different devices; when the first device is a network side device, the When the second device is a terminal, the second model is used to process the channel characteristic information obtained by the first device; or when the first device is a terminal and the second device is a network side device , the second model is used to process channel information.
可选的,模型匹配装置50还包括:Optionally, the model matching device 50 also includes:
第一接收模块,用于接收所述第二信道信息的标识;A first receiving module, configured to receive the identification of the second channel information;
第一确定模块,用于根据所述第二信道信息的标识,确定与所述第一信道特征信息对应的所述第二信道信息。A first determination module, configured to determine the second channel information corresponding to the first channel characteristic information according to the identification of the second channel information.
可选的,模型匹配装置50还包括:Optionally, the model matching device 50 also includes:
第二确定模块,用于根据所述第一信道特征信息的时频域位置,确定与所述第一信道特征信息对应的所述第二信道信息。The second determination module is configured to determine the second channel information corresponding to the first channel characteristic information according to the time-frequency domain position of the first channel characteristic information.
可选的,所述时频域位置由网络侧配置。Optionally, the time-frequency domain position is configured by the network side.
可选的,所述第一信道信息和所述第二信道信息为第一数据集中的信道信息,所述第一数据集中的信道信息用于进行模型匹配。Optionally, the first channel information and the second channel information are channel information in a first data set, and the channel information in the first data set is used for model matching.
可选的,所述第一信道信息和所述第二信道信息在所述第一数据集包含的信道信息中的顺序由协议约定或者网络侧配置。Optionally, the order of the first channel information and the second channel information in the channel information contained in the first data set is agreed upon by the protocol or configured by the network side.
可选的,模型匹配装置50还包括:Optionally, the model matching device 50 also includes:
第二接收模块,用于从所述第二设备接收所述第一数据集。A second receiving module, configured to receive the first data set from the second device.
可选的,所述第一数据集满足以下至少一项:Optionally, the first data set satisfies at least one of the following:
由终端采集;Collected by terminal;
由网络侧设备采集;Collected by network side equipment;
由协议约定;stipulated by agreement;
由网络侧设备指示的第二数据集中的子集,所述第二数据集被划分为多个子集;A subset of the second data set indicated by the network side device, the second data set being divided into a plurality of subsets;
由不同于所述第一设备和所述第二设备的第三设备提供。Provided by a third device different from the first device and the second device.
可选的,当所述第一数据集为由网络侧设备指示的第二数据集中的子集时,若所述第一设备为终端,模型匹配装置50还包括:Optionally, when the first data set is a subset of the second data set indicated by the network side device, and if the first device is a terminal, the model matching device 50 further includes:
第三接收模块,用于接收所述网络侧设备的配置信息,所述配置信息用于配置所述第一数据集的标识;A third receiving module, configured to receive configuration information of the network side device, where the configuration information is used to configure the identification of the first data set;
选择模块,用于根据所述第一数据集的标识,从所述第二数据集中选择所述第一数据集。A selection module, configured to select the first data set from the second data set according to the identification of the first data set.
可选的,当所述第一数据集由不同于所述第一设备和所述第二设备的第三设备提供时,模型匹配装置50还包括:Optionally, when the first data set is provided by a third device different from the first device and the second device, the model matching device 50 further includes:
第一执行模型,用于在所述第一数据集更新后,执行以下任一项:与所述第二设备和/或所述第三设备交互更新后的第一数据集的版本,与所述第二设备和/或所述第三设备交
互更新后的第一数据集;A first execution model, configured to perform any of the following after the first data set is updated: interact with the updated version of the first data set with the second device and/or the third device, interact with the The second device and/or the third device communicate The first data set after mutual updates;
所述匹配模块52还用于:利用更新后的第一数据集进行模型匹配。The matching module 52 is also configured to perform model matching using the updated first data set.
和/或,在所述第一数据集更新后,更新后的第一数据集和/或更新后的第一数据集的版本可以在所述第三设备与所述第二设备之间交互。And/or, after the first data set is updated, the updated first data set and/or the updated version of the first data set may be interacted between the third device and the second device.
可选的,当所述第二数据集由不同于所述第一设备和所述第二设备的第三设备提供时,模型匹配装置50还包括:Optionally, when the second data set is provided by a third device different from the first device and the second device, the model matching device 50 further includes:
第二执行模型,用于在所述第二数据集更新后,执行以下任一项:与所述第二设备和/或所述第三设备交互更新后的第二数据集的版本,与所述第二设备和/或所述第三设备交互更新后的第二数据集。A second execution model, configured to perform any of the following after the second data set is updated: interact with the updated version of the second data set with the second device and/or the third device; The second device and/or the third device interact with the updated second data set.
和/或,在所述第二数据集更新后,更新后的第二数据集和/或更新后的第二数据集的版本可以在所述第三设备与所述第二设备之间交互。And/or, after the second data set is updated, the updated second data set and/or the updated version of the second data set may be interacted between the third device and the second device.
可选的,当所述第一设备为网络侧设备,所述第二设备为终端时,所述匹配模块52用于以下至少一项:Optionally, when the first device is a network-side device and the second device is a terminal, the matching module 52 is used for at least one of the following:
将所述第一信道特征信息作为所述第二模型的输入,并将所述第二信道信息作为所述第二模型的输出,重新训练所述第二模型;Use the first channel characteristic information as the input of the second model, use the second channel information as the output of the second model, and retrain the second model;
根据所述第一信道特征信息以及所述第二信道信息,调整所述第二模型的参数。Adjust parameters of the second model according to the first channel characteristic information and the second channel information.
可选的,当所述第一设备为终端,所述第二设备为网络侧设备时,所述匹配模块52用于以下至少一项:Optionally, when the first device is a terminal and the second device is a network-side device, the matching module 52 is used for at least one of the following:
将所述第一信道特征信息作为所述第二模型的输出,并将所述第二信道信息作为所述第二模型的输入,重新训练所述第二模型;Use the first channel characteristic information as the output of the second model, use the second channel information as the input of the second model, and retrain the second model;
根据所述第一信道特征信息以及所述第二信道信息,调整所述第二模型的参数。Adjust parameters of the second model according to the first channel characteristic information and the second channel information.
本申请实施例提供的模型匹配装置50能够实现图4的方法实施例实现的各个过程,并达到相同的技术效果,为避免重复,这里不再赘述。The model matching device 50 provided by the embodiment of the present application can implement each process implemented by the method embodiment in Figure 4 and achieve the same technical effect. To avoid duplication, details will not be described here.
可选的,如图6所示,本申请实施例还提供一种通信设备60,包括处理器61和存储器62,存储器62上存储有可在所述处理器61上运行的程序或指令,该程序或指令被处理器61执行时可实现上述模型匹配方法实施例的各个步骤,且能达到相同的技术效果,为避免重复,这里不再赘述。该通信设备60可选为终端或者网络侧设备,该网络侧设备比如为基站或核心网设备。Optionally, as shown in Figure 6, this embodiment of the present application also provides a communication device 60, which includes a processor 61 and a memory 62. The memory 62 stores programs or instructions that can be run on the processor 61. When the program or instruction is executed by the processor 61, each step of the above model matching method embodiment can be implemented, and the same technical effect can be achieved. To avoid duplication, the details will not be described here. The communication device 60 may be a terminal or a network side device, such as a base station or a core network device.
本申请实施例还提供一种通信设备,该通信设备为第一设备,包括处理器和通信接口,处理器用于获取第一信道特征信息,所述第一信道特征信息是第二设备利用第一模型对第一信道信息进行处理得到;根据所述第一信道特征信息以及与所述第一信道特征信息对应的第二信道信息,对所述第一设备的第二模型与所述第一模型进行匹配;所述第一信道信息与所述第二信道信息相同;所述第一模型和所述第二模型是在不同设备中训练得到的模型;当所述第一设备为网络侧设备,所述第二设备为终端时,所述第二模型用于对所述第一设备获取的信道特征信息进行处理;或者,当所述第一设备为终端,所述第二设备为网
络侧设备时,所述第二模型用于对信道信息进行处理。该实施例与上述方法实施例对应,上述方法实施例的各个实施过程和实现方式均可适用于该实施例中,且能达到相同的技术效果。An embodiment of the present application also provides a communication device. The communication device is a first device and includes a processor and a communication interface. The processor is configured to obtain first channel characteristic information. The first channel characteristic information is obtained by the second device using the first The model is obtained by processing the first channel information; according to the first channel characteristic information and the second channel information corresponding to the first channel characteristic information, the second model of the first device and the first model are Matching is performed; the first channel information is the same as the second channel information; the first model and the second model are models trained in different devices; when the first device is a network side device, When the second device is a terminal, the second model is used to process the channel characteristic information obtained by the first device; or when the first device is a terminal, the second device is a network When using a network side device, the second model is used to process channel information. This embodiment corresponds to the above-mentioned method embodiment. Each implementation process and implementation manner of the above-mentioned method embodiment can be applied to this embodiment and can achieve the same technical effect.
具体地,图7为实现本申请实施例的一种终端的硬件结构示意图。Specifically, FIG. 7 is a schematic diagram of the hardware structure of a terminal that implements an embodiment of the present application.
该终端700包括但不限于:射频单元701、网络模块702、音频输出单元703、输入单元704、传感器705、显示单元706、用户输入单元707、接口单元708、存储器709以及处理器710等中的至少部分部件。The terminal 700 includes but is not limited to: a radio frequency unit 701, a network module 702, an audio output unit 703, an input unit 704, a sensor 705, a display unit 706, a user input unit 707, an interface unit 708, a memory 709, a processor 710, etc. At least some parts.
本领域技术人员可以理解,终端700还可以包括给各个部件供电的电源(比如电池),电源可以通过电源管理***与处理器710逻辑相连,从而通过电源管理***实现管理充电、放电、以及功耗管理等功能。图7中示出的终端结构并不构成对终端的限定,终端可以包括比图示更多或更少的部件,或者组合某些部件,或者不同的部件布置,在此不再赘述。Those skilled in the art can understand that the terminal 700 may also include a power supply (such as a battery) that supplies power to various components. The power supply may be logically connected to the processor 710 through a power management system, thereby managing charging, discharging, and power consumption through the power management system. Management and other functions. The terminal structure shown in FIG. 7 does not constitute a limitation on the terminal. The terminal may include more or fewer components than shown in the figure, or some components may be combined or arranged differently, which will not be described again here.
应理解的是,本申请实施例中,输入单元704可以包括图形处理单元(Graphics Processing Unit,GPU)7041和麦克风7042,图形处理器7041对在视频捕获模式或图像捕获模式中由图像捕获装置(如摄像头)获得的静态图片或视频的图像数据进行处理。显示单元706可包括显示面板7061,可以采用液晶显示器、有机发光二极管等形式来配置显示面板7061。用户输入单元707包括触控面板7071以及其他输入设备7072中的至少一种。触控面板7071,也称为触摸屏。触控面板7071可包括触摸检测装置和触摸控制器两个部分。其他输入设备7072可以包括但不限于物理键盘、功能键(比如音量控制按键、开关按键等)、轨迹球、鼠标、操作杆,在此不再赘述。It should be understood that in the embodiment of the present application, the input unit 704 may include a graphics processing unit (Graphics Processing Unit, GPU) 7041 and a microphone 7042. The graphics processor 7041 is responsible for the image capture device (GPU) in the video capture mode or the image capture mode. Process the image data of still pictures or videos obtained by cameras (such as cameras). The display unit 706 may include a display panel 7061, which may be configured in the form of a liquid crystal display, an organic light emitting diode, or the like. The user input unit 707 includes a touch panel 7071 and at least one of other input devices 7072 . Touch panel 7071, also called touch screen. The touch panel 7071 may include two parts: a touch detection device and a touch controller. Other input devices 7072 may include but are not limited to physical keyboards, function keys (such as volume control keys, switch keys, etc.), trackballs, mice, and joysticks, which will not be described again here.
本申请实施例中,射频单元701接收来自网络侧设备的下行数据后,可以传输给处理器710进行处理;另外,射频单元701可以向网络侧设备发送上行数据。通常,射频单元701包括但不限于天线、放大器、收发信机、耦合器、低噪声放大器、双工器等。In this embodiment of the present application, after receiving downlink data from the network side device, the radio frequency unit 701 can transmit it to the processor 710 for processing; in addition, the radio frequency unit 701 can send uplink data to the network side device. Generally, the radio frequency unit 701 includes, but is not limited to, an antenna, amplifier, transceiver, coupler, low noise amplifier, duplexer, etc.
存储器709可用于存储软件程序或指令以及各种数据。存储器709可主要包括存储程序或指令的第一存储区和存储数据的第二存储区,其中,第一存储区可存储操作***、至少一个功能所需的应用程序或指令(比如声音播放功能、图像播放功能等)等。此外,存储器709可以包括易失性存储器或非易失性存储器,或者,存储器709可以包括易失性和非易失性存储器两者。其中,非易失性存储器可以是只读存储器(Read-Only Memory,ROM)、可编程只读存储器(Programmable ROM,PROM)、可擦除可编程只读存储器(Erasable PROM,EPROM)、电可擦除可编程只读存储器(Electrically EPROM,EEPROM)或闪存。易失性存储器可以是随机存取存储器(Random Access Memory,RAM),静态随机存取存储器(Static RAM,SRAM)、动态随机存取存储器(Dynamic RAM,DRAM)、同步动态随机存取存储器(Synchronous DRAM,SDRAM)、双倍数据速率同步动态随机存取存储器(Double Data Rate SDRAM,DDRSDRAM)、增强型同步动态随机存取存储器(Enhanced SDRAM,ESDRAM)、同步连接动态随机存取存储器(Synch link DRAM,SLDRAM)和直接内存总线随机存取存储器(Direct Rambus RAM,DRRAM)。本申请实施例中的存储器709包括但不
限于这些和任意其它适合类型的存储器。Memory 709 may be used to store software programs or instructions as well as various data. The memory 709 may mainly include a first storage area for storing programs or instructions and a second storage area for storing data, wherein the first storage area may store an operating system, an application program or instructions required for at least one function (such as a sound playback function, Image playback function, etc.) etc. Additionally, memory 709 may include volatile memory or non-volatile memory, or memory 709 may include both volatile and non-volatile memory. Among them, the non-volatile memory can be read-only memory (Read-Only Memory, ROM), programmable read-only memory (Programmable ROM, PROM), erasable programmable read-only memory (Erasable PROM, EPROM), electrically removable memory. Erase programmable read-only memory (Electrically EPROM, EEPROM) or flash memory. Volatile memory can be random access memory (Random Access Memory, RAM), static random access memory (Static RAM, SRAM), dynamic random access memory (Dynamic RAM, DRAM), synchronous dynamic random access memory (Synchronous DRAM, SDRAM), double data rate synchronous dynamic random access memory (Double Data Rate SDRAM, DDRSDRAM), enhanced synchronous dynamic random access memory (Enhanced SDRAM, ESDRAM), synchronous link dynamic random access memory (Synch link DRAM) , SLDRAM) and direct memory bus random access memory (Direct Rambus RAM, DRRAM). The memory 709 in the embodiment of this application includes but does not Limited to these and any other suitable types of memory.
处理器710可包括一个或多个处理单元;可选的,处理器710集成应用处理器和调制解调处理器,其中,应用处理器主要处理涉及操作***、用户界面和应用程序等的操作,调制解调处理器主要处理无线通信信号,如基带处理器。可以理解的是,上述调制解调处理器也可以不集成到处理器710中。The processor 710 may include one or more processing units; optionally, the processor 710 integrates an application processor and a modem processor, where the application processor mainly handles operations related to the operating system, user interface, application programs, etc., Modem processors mainly process wireless communication signals, such as baseband processors. It can be understood that the above-mentioned modem processor may not be integrated into the processor 710.
其中,处理器710,用于获取第一信道特征信息,所述第一信道特征信息是网络侧设备利用第一模型对第一信道信息进行处理得到;根据所述第一信道特征信息以及与第一信道特征信息对应的第二信道信息,对终端700中的第二模型与所述第一模型进行匹配;所述第一信道信息与所述第二信道信息相同;所述第一模型和所述第二模型是在不同设备中训练得到的模型;所述第二模型用于对信道信息进行处理。Among them, the processor 710 is used to obtain the first channel characteristic information, which is obtained by processing the first channel information by the network side device using the first model; according to the first channel characteristic information and the first channel characteristic information, The second channel information corresponding to the channel characteristic information matches the second model in the terminal 700 with the first model; the first channel information is the same as the second channel information; the first model is the same as the second channel information. The second model is a model trained in different devices; the second model is used to process channel information.
本申请实施例提供的终端700能够实现图4的方法实施例中终端实现的各个过程,并达到相同的技术效果,为避免重复,这里不再赘述。The terminal 700 provided by the embodiment of the present application can implement each process implemented by the terminal in the method embodiment of Figure 4 and achieve the same technical effect. To avoid duplication, details will not be described here.
具体地,本申请实施例还提供了一种网络侧设备。如图8所示,该网络侧设备80包括:处理器81、网络接口82和存储器83。其中,网络接口82例如为通用公共无线接口(common public radio interface,CPRI)。Specifically, the embodiment of the present application also provides a network side device. As shown in FIG. 8 , the network side device 80 includes: a processor 81 , a network interface 82 and a memory 83 . Among them, the network interface 82 is, for example, a common public radio interface (CPRI).
具体地,本发明实施例的网络侧设备80还包括:存储在存储器83上并可在处理器81上运行的指令或程序,处理器81调用存储器83中的指令或程序执行图5中所示各模块执行的方法,并达到相同的技术效果,为避免重复,故不在此赘述。Specifically, the network side device 80 in this embodiment of the present invention also includes: instructions or programs stored in the memory 83 and executable on the processor 81. The processor 81 calls the instructions or programs in the memory 83 to execute what is shown in Figure 5 To avoid duplication, the methods for executing each module and achieving the same technical effect will not be described in detail here.
本申请实施例还提供一种可读存储介质,所述可读存储介质上存储有程序或指令,该程序或指令被处理器执行时实现上述模型匹配方法实施例的各个过程,且能达到相同的技术效果,为避免重复,这里不再赘述。Embodiments of the present application also provide a readable storage medium. Programs or instructions are stored on the readable storage medium. When the program or instructions are executed by a processor, each process of the above model matching method embodiment is implemented, and the same can be achieved. The technical effects will not be repeated here to avoid repetition.
其中,该处理器为上述实施例中所述的终端中的处理器。该可读存储介质,包括计算机可读存储介质,如计算机只读存储器ROM、随机存取存储器RAM、磁碟或者光盘等。Wherein, the processor is the processor in the terminal described in the above embodiment. The readable storage medium includes computer readable storage media, such as computer read-only memory ROM, random access memory RAM, magnetic disk or optical disk, etc.
本申请实施例另提供了一种芯片,所述芯片包括处理器和通信接口,所述通信接口和所述处理器耦合,所述处理器用于运行程序或指令,实现上述模型匹配方法实施例的各个过程,且能达到相同的技术效果,为避免重复,这里不再赘述。An embodiment of the present application further provides a chip. The chip includes a processor and a communication interface. The communication interface is coupled to the processor. The processor is used to run programs or instructions to implement the above model matching method embodiment. Each process can achieve the same technical effect. To avoid duplication, it will not be described again here.
应理解,本申请实施例提到的芯片还可以称为***级芯片,***芯片,芯片***或片上***芯片等。It should be understood that the chips mentioned in the embodiments of this application may also be called system-on-chip, system-on-a-chip, system-on-chip or system-on-chip, etc.
本申请实施例另提供了一种计算机程序/程序产品,所述计算机程序/程序产品被存储在存储介质中,所述计算机程序/程序产品被至少一个处理器执行以实现上述模型匹配方法实施例的各个过程,且能达到相同的技术效果,为避免重复,这里不再赘述。Embodiments of the present application further provide a computer program/program product. The computer program/program product is stored in a storage medium. The computer program/program product is executed by at least one processor to implement the above model matching method embodiment. Each process can achieve the same technical effect. To avoid repetition, we will not go into details here.
本申请实施例还提供了一种通信***,包括:第一设备及第二设备,所述第一设备可用于执行如上所述的模型匹配方法的步骤,所述第二设备可利用第一模型对第一信道信息进行处理,得到第一信道特征信息,并发送所述第一信道特征信息至第一设备。An embodiment of the present application also provides a communication system, including: a first device and a second device. The first device can be used to perform the steps of the model matching method as described above. The second device can utilize the first model. Process the first channel information to obtain first channel characteristic information, and send the first channel characteristic information to the first device.
需要说明的是,在本文中,术语“包括”、“包含”或者其任何其他变体意在涵盖非排
他性的包含,从而使得包括一系列要素的过程、方法、物品或者装置不仅包括那些要素,而且还包括没有明确列出的其他要素,或者是还包括为这种过程、方法、物品或者装置所固有的要素。在没有更多限制的情况下,由语句“包括一个……”限定的要素,并不排除在包括该要素的过程、方法、物品或者装置中还存在另外的相同要素。此外,需要指出的是,本申请实施方式中的方法和装置的范围不限按示出或讨论的顺序来执行功能,还可包括根据所涉及的功能按基本同时的方式或按相反的顺序来执行功能,例如,可以按不同于所描述的次序来执行所描述的方法,并且还可以添加、省去、或组合各种步骤。另外,参照某些示例所描述的特征可在其他示例中被组合。It should be noted that in this article, the terms "include", "include" or any other variation thereof are intended to cover non-exclusive Other inclusion, such that a process, method, article, or device that includes a list of elements includes not only those elements, but also other elements not expressly listed, or that is included for such process, method, article, or device inherent elements. Without further limitation, an element defined by the statement "comprises a..." does not exclude the presence of additional identical elements in a process, method, article or apparatus that includes that element. In addition, it should be pointed out that the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, but may also include performing functions in a substantially simultaneous manner or in reverse order according to the functions involved. Functions may be performed, for example, the methods described may be performed in an order different from that described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.
通过以上的实施方式的描述,本领域的技术人员可以清楚地了解到上述实施例方法可借助软件加必需的通用硬件平台的方式来实现,当然也可以通过硬件,但很多情况下前者是更佳的实施方式。基于这样的理解,本申请的技术方案本质上或者说对现有技术做出贡献的部分可以以计算机软件产品的形式体现出来,该计算机软件产品存储在一个存储介质(如ROM/RAM、磁碟、光盘)中,包括若干指令用以使得一台终端(可以是手机,计算机,服务器,空调器,或者网络设备等)执行本申请各个实施例所述的方法。Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus the necessary general hardware platform. Of course, it can also be implemented by hardware, but in many cases the former is better. implementation. Based on this understanding, the technical solution of the present application can be embodied in the form of a computer software product that is essentially or contributes to the existing technology. The computer software product is stored in a storage medium (such as ROM/RAM, disk , CD), including several instructions to cause a terminal (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in various embodiments of this application.
上面结合附图对本申请的实施例进行了描述,但是本申请并不局限于上述的具体实施方式,上述的具体实施方式仅仅是示意性的,而不是限制性的,本领域的普通技术人员在本申请的启示下,在不脱离本申请宗旨和权利要求所保护的范围情况下,还可做出很多形式,均属于本申请的保护之内。
The embodiments of the present application have been described above in conjunction with the accompanying drawings. However, the present application is not limited to the above-mentioned specific implementations. The above-mentioned specific implementations are only illustrative and not restrictive. Those of ordinary skill in the art will Inspired by this application, many forms can be made without departing from the purpose of this application and the scope protected by the claims, all of which fall within the protection of this application.
Claims (16)
- 一种模型匹配方法,包括:A model matching method including:第一设备获取第一信道特征信息,所述第一信道特征信息是第二设备利用第一模型对第一信道信息进行处理得到;The first device acquires first channel characteristic information, which is obtained by the second device using the first model to process the first channel information;所述第一设备根据所述第一信道特征信息以及与所述第一信道特征信息对应的第二信道信息,对所述第一设备的第二模型与所述第一模型进行匹配;The first device matches the second model of the first device with the first model according to the first channel characteristic information and the second channel information corresponding to the first channel characteristic information;其中,所述第一信道信息与所述第二信道信息相同;所述第一模型和所述第二模型是在不同设备中训练得到的模型;当所述第一设备为网络侧设备,所述第二设备为终端时,所述第二模型用于对所述第一设备获取的信道特征信息进行处理;或者,当所述第一设备为终端,所述第二设备为网络侧设备时,所述第二模型用于对信道信息进行处理。Wherein, the first channel information is the same as the second channel information; the first model and the second model are models trained in different devices; when the first device is a network side device, the When the second device is a terminal, the second model is used to process the channel characteristic information obtained by the first device; or when the first device is a terminal and the second device is a network side device , the second model is used to process channel information.
- 根据权利要求1所述的方法,其中,所述根据所述第一信道特征信息以及与所述第一信道特征信息对应的第二信道信息,对所述第一设备的第二模型与所述第一模型进行匹配之前,所述方法还包括:The method according to claim 1, wherein, according to the first channel characteristic information and the second channel information corresponding to the first channel characteristic information, the second model of the first device and the Before matching the first model, the method further includes:所述第一设备接收所述第二信道信息的标识;The first device receives the identification of the second channel information;所述第一设备根据所述第二信道信息的标识,确定与所述第一信道特征信息对应的所述第二信道信息。The first device determines the second channel information corresponding to the first channel characteristic information according to the identification of the second channel information.
- 根据权利要求1所述的方法,其中,所述根据所述第一信道特征信息以及与所述第一信道特征信息对应的第二信道信息,对所述第一设备的第二模型与所述第一模型进行匹配之前,所述方法还包括:The method according to claim 1, wherein, according to the first channel characteristic information and the second channel information corresponding to the first channel characteristic information, the second model of the first device and the Before matching the first model, the method further includes:所述第一设备根据所述第一信道特征信息的时频域位置,确定与所述第一信道特征信息对应的所述第二信道信息。The first device determines the second channel information corresponding to the first channel characteristic information based on the time-frequency domain position of the first channel characteristic information.
- 根据权利要求3所述的方法,其中,所述时频域位置由网络侧配置。The method according to claim 3, wherein the time-frequency domain location is configured by the network side.
- 根据权利要求1至4任一项所述的方法,其中,所述第一信道信息和所述第二信道信息为第一数据集中的信道信息,所述第一数据集中的信道信息用于进行模型匹配。The method according to any one of claims 1 to 4, wherein the first channel information and the second channel information are channel information in a first data set, and the channel information in the first data set is used to perform Model matching.
- 根据权利要求5所述的方法,其中,所述第一信道信息和所述第二信道信息在所述第一数据集包含的信道信息中的顺序由协议约定或者网络侧配置。The method according to claim 5, wherein the order of the first channel information and the second channel information in the channel information contained in the first data set is agreed by a protocol or configured by the network side.
- 根据权利要求5所述的方法,其中,所述方法还包括:The method of claim 5, further comprising:所述第一设备从所述第二设备接收所述第一数据集。The first device receives the first data set from the second device.
- 根据权利要求5任一项所述的方法,其中,所述第一数据集满足以下至少一项:The method according to any one of claims 5, wherein the first data set satisfies at least one of the following:由终端采集;Collected by terminal;由网络侧设备采集;Collected by network side equipment;由协议约定;stipulated by agreement;由网络侧设备指示的第二数据集中的子集,所述第二数据集被划分为多个子集;A subset of the second data set indicated by the network side device, the second data set being divided into a plurality of subsets;由不同于所述第一设备和所述第二设备的第三设备提供。 Provided by a third device different from the first device and the second device.
- 根据权利要求8所述的方法,其中,当所述第一数据集为由网络侧设备指示的第二数据集中的子集时,若所述第一设备为终端,所述方法还包括:The method according to claim 8, wherein when the first data set is a subset of the second data set indicated by the network side device, if the first device is a terminal, the method further includes:所述终端接收所述网络侧设备的配置信息,所述配置信息用于配置所述第一数据集的标识;The terminal receives configuration information of the network side device, where the configuration information is used to configure the identification of the first data set;所述终端根据所述第一数据集的标识,从所述第二数据集中选择所述第一数据集。The terminal selects the first data set from the second data set according to the identification of the first data set.
- 根据权利要求8所述的方法,其中,当所述第一数据集由不同于所述第一设备和所述第二设备的第三设备提供时,在所述第一数据集更新后,所述方法还包括:The method of claim 8, wherein when the first data set is provided by a third device different from the first device and the second device, after the first data set is updated, the The above methods also include:所述第一设备执行以下任一项:与所述第二设备和/或所述第三设备交互更新后的第一数据集的版本,与所述第二设备和/或所述第三设备交互更新后的第一数据集;The first device performs any of the following: interacting with the updated version of the first data set with the second device and/or the third device, communicating with the second device and/or the third device The first data set after interactive update;所述第一设备利用更新后的第一数据集进行模型匹配;The first device uses the updated first data set to perform model matching;和/或,and / or,在所述第一数据集更新后,更新后的第一数据集和/或更新后的第一数据集的版本,在所述第三设备与所述第二设备之间交互。After the first data set is updated, the updated first data set and/or the updated version of the first data set is interacted between the third device and the second device.
- 根据权利要求8或9所述的方法,其中,当所述第二数据集由不同于所述第一设备和所述第二设备的第三设备提供时,在所述第二数据集更新后,所述方法还包括:The method of claim 8 or 9, wherein when the second data set is provided by a third device different from the first device and the second device, after the second data set is updated , the method also includes:所述第一设备执行以下任一项:与所述第二设备和/或所述第三设备交互更新后的第二数据集的版本,与所述第二设备和/或所述第三设备交互更新后的第二数据集;The first device performs any of the following: interacting with the updated version of the second data set with the second device and/or the third device, communicating with the second device and/or the third device The interactively updated second data set;和/或,and / or,在所述第二数据集更新后,更新后的第二数据集和/或更新后的第二数据集的版本,在所述第三设备与所述第二设备之间交互。After the second data set is updated, the updated second data set and/or the updated version of the second data set is interacted between the third device and the second device.
- 根据权利要求1所述的方法,其中,当所述第一设备为网络侧设备,所述第二设备为终端时,所述根据所述第一信道特征信息以及与所述第一信道特征信息对应的第二信道信息,对所述第一设备的第二模型与所述第一模型进行匹配,包括以下至少一项:The method according to claim 1, wherein when the first device is a network side device and the second device is a terminal, the method according to the first channel characteristic information and the first channel characteristic information The corresponding second channel information matches the second model of the first device with the first model, including at least one of the following:所述第一设备将所述第一信道特征信息作为所述第二模型的输入,并将所述第二信道信息作为所述第二模型的输出,重新训练所述第二模型;The first device uses the first channel characteristic information as an input to the second model, uses the second channel information as an output of the second model, and retrains the second model;所述第一设备根据所述第一信道特征信息以及所述第二信道信息,调整所述第二模型的参数。The first device adjusts parameters of the second model according to the first channel characteristic information and the second channel information.
- 根据权利要求1所述的方法,其中,当所述第一设备为终端,所述第二设备为网络侧设备时,所述根据所述第一信道特征信息以及与所述第一信道特征信息对应的第二信道信息,对所述第一设备的第二模型与所述第一模型进行匹配,包括以下至少一项:The method according to claim 1, wherein when the first device is a terminal and the second device is a network side device, the method according to the first channel characteristic information and the first channel characteristic information The corresponding second channel information matches the second model of the first device with the first model, including at least one of the following:所述第一设备将所述第一信道特征信息作为所述第二模型的输出,并将所述第二信道信息作为所述第二模型的输入,重新训练所述第二模型;The first device uses the first channel characteristic information as an output of the second model, uses the second channel information as an input of the second model, and retrains the second model;所述第一设备根据所述第一信道特征信息以及所述第二信道信息,调整所述第二模型的参数。The first device adjusts parameters of the second model according to the first channel characteristic information and the second channel information.
- 一种模型匹配装置,包括: A model matching device including:获取模块,用于获取第一信道特征信息,所述第一信道特征信息是第二设备利用第一模型对第一信道信息进行处理得到;An acquisition module, configured to acquire first channel characteristic information, which is obtained by processing the first channel information by the second device using the first model;匹配模块,用于根据所述第一信道特征信息以及与所述第一信道特征信息对应的第二信道信息,对第一设备的第二模型与所述第一模型进行匹配;A matching module configured to match the second model of the first device with the first model according to the first channel characteristic information and the second channel information corresponding to the first channel characteristic information;其中,所述第一信道信息与所述第二信道信息相同;所述第一模型和所述第二模型是在不同设备中训练得到的模型;当所述第一设备为网络侧设备,所述第二设备为终端时,所述第二模型用于对所述第一设备获取的信道特征信息进行处理;或者,当所述第一设备为终端,所述第二设备为网络侧设备时,所述第二模型用于对信道信息进行处理。Wherein, the first channel information is the same as the second channel information; the first model and the second model are models trained in different devices; when the first device is a network side device, the When the second device is a terminal, the second model is used to process the channel characteristic information obtained by the first device; or when the first device is a terminal and the second device is a network side device , the second model is used to process channel information.
- 一种通信设备,包括处理器和存储器,所述存储器存储可在所述处理器上运行的程序或指令,所述程序或指令被所述处理器执行时实现如权利要求1至13任一项所述的模型匹配方法的步骤。A communication device, including a processor and a memory. The memory stores programs or instructions that can be run on the processor. When the program or instructions are executed by the processor, the implementation of any one of claims 1 to 13 is achieved. The steps of the model matching method.
- 一种可读存储介质,所述可读存储介质上存储程序或指令,所述程序或指令被处理器执行时实现如权利要求1至13任一项所述的模型匹配方法的步骤。 A readable storage medium on which a program or instructions are stored, and when the program or instructions are executed by a processor, the steps of the model matching method according to any one of claims 1 to 13 are implemented.
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202210934857.5 | 2022-08-04 | ||
CN202210934857.5A CN117579201A (en) | 2022-08-04 | 2022-08-04 | Model matching method, device, communication equipment and readable storage medium |
Publications (1)
Publication Number | Publication Date |
---|---|
WO2024027683A1 true WO2024027683A1 (en) | 2024-02-08 |
Family
ID=89848560
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
PCT/CN2023/110481 WO2024027683A1 (en) | 2022-08-04 | 2023-08-01 | Model matching method and apparatus, communication device, and readable storage medium |
Country Status (2)
Country | Link |
---|---|
CN (1) | CN117579201A (en) |
WO (1) | WO2024027683A1 (en) |
Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20110255613A1 (en) * | 2010-04-15 | 2011-10-20 | Futurewei Technologies, Inc. | System and Method for Feeding Back Channel Information |
US20210273707A1 (en) * | 2020-02-28 | 2021-09-02 | Qualcomm Incorporated | Neural network based channel state information feedback |
CN113810086A (en) * | 2020-06-12 | 2021-12-17 | 华为技术有限公司 | Channel information feedback method, communication device and storage medium |
CN113938907A (en) * | 2020-07-13 | 2022-01-14 | 华为技术有限公司 | Communication method and communication device |
CN114172615A (en) * | 2020-09-11 | 2022-03-11 | 维沃移动通信有限公司 | Transmission method, device, equipment and readable storage medium |
CN114679355A (en) * | 2020-12-24 | 2022-06-28 | 华为技术有限公司 | Communication method and device |
-
2022
- 2022-08-04 CN CN202210934857.5A patent/CN117579201A/en active Pending
-
2023
- 2023-08-01 WO PCT/CN2023/110481 patent/WO2024027683A1/en unknown
Patent Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20110255613A1 (en) * | 2010-04-15 | 2011-10-20 | Futurewei Technologies, Inc. | System and Method for Feeding Back Channel Information |
US20210273707A1 (en) * | 2020-02-28 | 2021-09-02 | Qualcomm Incorporated | Neural network based channel state information feedback |
CN113810086A (en) * | 2020-06-12 | 2021-12-17 | 华为技术有限公司 | Channel information feedback method, communication device and storage medium |
CN113938907A (en) * | 2020-07-13 | 2022-01-14 | 华为技术有限公司 | Communication method and communication device |
CN114172615A (en) * | 2020-09-11 | 2022-03-11 | 维沃移动通信有限公司 | Transmission method, device, equipment and readable storage medium |
CN114679355A (en) * | 2020-12-24 | 2022-06-28 | 华为技术有限公司 | Communication method and device |
Also Published As
Publication number | Publication date |
---|---|
CN117579201A (en) | 2024-02-20 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
WO2024027683A1 (en) | Model matching method and apparatus, communication device, and readable storage medium | |
WO2024032694A1 (en) | Csi prediction processing method and apparatus, communication device, and readable storage medium | |
WO2024037380A1 (en) | Channel information processing methods and apparatus, communication device, and storage medium | |
WO2024104126A1 (en) | Method and apparatus for updating ai network model, and communication device | |
WO2024032606A1 (en) | Information transmission method and apparatus, device, system, and storage medium | |
WO2024067280A1 (en) | Method and apparatus for updating ai model parameter, and communication device | |
WO2024041421A1 (en) | Measurement feedback processing method and apparatus, terminal, and network side device | |
WO2024067665A1 (en) | Csi prediction processing method and apparatus, and communication device and readable storage medium | |
WO2023179570A1 (en) | Channel feature information transmission method and apparatus, terminal, and network side device | |
WO2024164962A1 (en) | Communication processing methods and apparatus, device, and readable storage medium | |
WO2024149156A1 (en) | Information transmission method and apparatus, and terminal and network-side device | |
WO2024067281A1 (en) | Ai model processing method and apparatus, and communication device | |
WO2024078405A1 (en) | Transmission methods, apparatus, communication device, and readable storage medium | |
WO2024120358A1 (en) | Information transmission method, information transmission apparatus, and communication device | |
WO2024125391A2 (en) | Ai model monitoring method and apparatus, ai model performance measurement method and apparatus, and device | |
WO2023186091A1 (en) | Sample determination method, apparatus and device | |
WO2024160085A1 (en) | Communication processing method and apparatus, device and readable storage medium | |
WO2024051564A1 (en) | Information transmission method, ai network model training method, apparatus, and communication device | |
WO2024012303A1 (en) | Ai network model interaction method and apparatus, and communication device | |
WO2023125934A1 (en) | Ai network information transmission method and apparatus, and communication device | |
WO2023098535A1 (en) | Information interaction method and apparatus, and communication device | |
WO2024140422A1 (en) | Ai unit performance monitoring method, terminal and network side device | |
WO2023179540A1 (en) | Channel prediction method and apparatus, and wireless communication device | |
WO2023109828A1 (en) | Data collection method and apparatus, and first device and second device | |
WO2024055993A1 (en) | Cqi transmission method and apparatus, and terminal and network-side device |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
121 | Ep: the epo has been informed by wipo that ep was designated in this application |
Ref document number: 23849390 Country of ref document: EP Kind code of ref document: A1 |