CN115967596A - Signal processing method, device and storage medium - Google Patents

Signal processing method, device and storage medium Download PDF

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Publication number
CN115967596A
CN115967596A CN202111183135.2A CN202111183135A CN115967596A CN 115967596 A CN115967596 A CN 115967596A CN 202111183135 A CN202111183135 A CN 202111183135A CN 115967596 A CN115967596 A CN 115967596A
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noise
information
nodes
node
channel
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史清江
赵小彤
李勉
管鑫
王勃
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Huawei Technologies Co Ltd
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Huawei Technologies Co Ltd
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Abstract

The application provides a signal processing method, a signal processing device and a storage medium, wherein the method comprises the following steps: a first node acquires channel parameters corresponding to P second nodes respectively, the channel parameters comprise channel information and first parameters, the first parameters comprise noise-related information or noise information, and the noise-related information is used for indicating M corresponding to the second nodes c Noise correlation between antennas, noise information indicating noise of a first signal received by a second node, P being an integer greater than 1, M c And the first node determines equalization information according to the channel parameters respectively corresponding to the P second nodes, wherein the equalization information is used for performing channel equalization on a second signal, and the second signal is determined according to the first signal respectively received by the P second nodes. Distributed equalization processing based on colored noise is achieved, and the data size of interaction between the nodes and the computational complexity of the first node are reduced.

Description

Signal processing method and device and storage medium
Technical Field
The present application relates to the field of communications technologies, and in particular, to a method and an apparatus for processing a signal, and a storage medium.
Background
In some communication systems, such as fifth generation mobile communication systems (5 g), multiple-in-multiple-out (MIMO) technology and very large scale multiple-input and multiple-output (XL-MIMO) technology, as core technologies of future mobile communication systems, the spectrum efficiency and energy efficiency of the mobile communication systems can be greatly improved. In this scenario, channel equalization techniques, such as Maximum Ratio Combining (MRC), zero Forcing (ZF), minimum Mean Square Error (MMSE), etc., may reduce crosstalk between user data streams of an uplink transmission link to ensure reception performance of a base station, which is a key technique for achieving high spectral efficiency and energy efficiency of XL-MIMO technology.
However, as the number of antennas of the network device increases, the network device performs centralized channel equalization on each antenna or each antenna sub-array, so that the amount of interactive data is large and the computational complexity is high, whereas in the existing distributed equalization technology, by using each distributed baseband processing unit in the network device and based on an MMSE equalization algorithm under white noise, multiple rounds of iteration are realized by performing data interaction between each distributed baseband processing unit to achieve the equalization effect of the centralized equalization algorithm, which shows that the distributed equalization technology still has the problems of large amount of interactive data and high computational complexity.
Disclosure of Invention
The signal processing method, device and storage medium provided by the embodiment of the application can reduce the processing complexity of the baseband signal and improve the information transmission efficiency.
In a first aspect, an embodiment of the present application provides a signal processing method, including: the first node obtains channel parameters corresponding to P second nodes respectively, and the channel parameters comprise channel information
Figure BDA0003298089410000011
And a first parameter comprising noise-related information ≥>
Figure BDA0003298089410000015
Or noise information->
Figure BDA0003298089410000013
The noise-related information->
Figure BDA0003298089410000012
M for indicating the second node corresponds to c Noise correlation between individual antennas, the noise information &>
Figure BDA0003298089410000014
For indicating the noise of the first signal received by the second node, P being an integer greater than 1, M c Is an integer greater than 0; the first node determines equalization information according to the channel parameters corresponding to the P second nodes, where the equalization information is used to perform channel equalization on a second signal, and the second signal is determined according to the first signals received by the P second nodes, respectively.
With the signal processing method provided by the first aspect, the channel parameters respectively corresponding to the P second nodes acquired by the first node carry M c And the first node determines equalization information based on the channel parameters and performs channel equalization according to the equalization information, so that distributed equalization processing based on colored noise is realized, and the interactive data volume between the nodes and the computational complexity of the first node are reduced.
In a possible implementation manner, the determining, by the first node, equalization information according to the channel parameters respectively corresponding to the P second nodes includes: the first node performs parameter fusion on the channel parameters respectively corresponding to the P second nodes to obtain equivalent parameters; the first node determines equalization information according to the equalization parameter.
By the signal processing method provided by the embodiment, the first node can determine the equalization information according to the fused equivalent parameters, so that the computational complexity is reduced, and the processing efficiency of the first node is improved.
In a possible implementation manner, the parameter fusion performed by the first node on the channel parameters corresponding to the P second nodes, to obtain the equivalent parameters includes: the first node respectively corresponds to the channel information of the P second nodes
Figure BDA0003298089410000021
Performing parameter fusion to obtain equivalent channel information->
Figure BDA0003298089410000022
And the first node judges the noise information corresponding to the P second nodes respectively>
Figure BDA0003298089410000023
Performing parameter fusion to obtain equivalent noise information->
Figure BDA0003298089410000024
Or the first node respectively corresponding noise related information of the P second nodes is/are judged by the first node>
Figure BDA0003298089410000025
Performing parameter fusion to obtain equivalent noise related information->
Figure BDA0003298089410000026
By the signal processing method provided by the embodiment, the first node performs parameter fusion on each channel parameter respectively to obtain the equivalent parameter of each channel parameter, so that the equalization information is prevented from being determined based on each channel parameter, the computational complexity is reduced, and the processing efficiency of the first node is improved.
In one possible embodiment, the method further comprises: the first node is based on the equivalent noise information
Figure BDA0003298089410000027
Determining equivalent noise-related information ≥>
Figure BDA0003298089410000028
In a possible implementation manner, the first node respectively corresponds to the channel information of the P second nodes
Figure BDA0003298089410000029
Performing parameter fusion to obtain equivalent channel information->
Figure BDA00032980894100000210
The method comprises the following steps: the first node judges the channel information corresponding to the P second nodes respectively>
Figure BDA00032980894100000211
Summing or matrix splicing is carried out to obtain the equivalent channel information->
Figure BDA00032980894100000212
In a possible implementation manner, the first node respectively corresponds to the noise information of the P second nodes
Figure BDA00032980894100000213
Performing parameter fusion to obtain equivalent noise information->
Figure BDA00032980894100000214
The method comprises the following steps: the first node combines the noise information corresponding to the P second nodes>
Figure BDA00032980894100000215
Summing or matrix splicing is carried out to obtain the equivalent noise information->
Figure BDA00032980894100000216
In a possible implementation manner, the first node respectively corresponds noise related information to the P second nodes
Figure BDA00032980894100000217
Performing parameter fusion to obtain equivalent noise related information->
Figure BDA00032980894100000218
The method comprises the following steps: the first node judges the noise related information corresponding to the P second nodes respectively>
Figure BDA00032980894100000219
Summing or matrix splicing is carried out to obtain the equivalent noise related information->
Figure BDA00032980894100000220
In one possible embodiment, the equalization information W H The following formula is satisfied:
Figure BDA00032980894100000221
in one possible embodiment, the channel parameters are compressed matrices
Figure BDA00032980894100000222
Weighted, compression matrix +>
Figure BDA00032980894100000223
Is determined based on the channel parameters.
In one possible embodiment, the compression matrix
Figure BDA00032980894100000224
Is L M c Dimension matrix, where L is H c The number of columns.
With the signal processing method provided by this embodiment, when L is greater than or equal to the channel information H c Can be lossless compressed when L is less than the channel information H c Is easy to cause signal loss, so when L is equal to the channel information H c The first node may implement a pair channelMaximum lossless compression of the parameter and/or the first signal.
In one possible embodiment, the compression matrix
Figure BDA00032980894100000225
The following formula is satisfied: />
Figure BDA00032980894100000226
Wherein H c For channel information before compression, R cc For noise-related information before compression
In one possible embodiment, the method further comprises: and the first node performs signal fusion on the first signals respectively received by the P second nodes to obtain the second signals.
In a possible implementation manner, the signal fusion of the first signals respectively received by the P second nodes by the first node to obtain the second signal includes: and the first node sums or matrix splices the first signals respectively received by the P second nodes to obtain the second signals.
According to the signal processing method provided by the embodiment related to parameter fusion, the channel parameter obtained by the first node through the summation strategy is lower in complexity in the subsequent processing process of determining the equalization information than the channel parameter obtained through the matrix splicing strategy, and the channel parameter obtained by the first node through the matrix splicing strategy is higher in performance of the subsequently determined equalization information than the channel parameter obtained through the summation strategy.
In one possible embodiment, the first signal is a compressed matrix
Figure BDA00032980894100000227
Weighted, the compression matrix->
Figure BDA00032980894100000228
Is determined based on the channel parameters.
By the signal processing method provided by the embodiment related to the compression matrix, the second node sends the channel parameters and/or the first signal compressed by the compression matrix to the first node, and the interactive data volume is further reduced.
In a possible implementation, the P second nodes include the first node and P-1 third nodes or the P second nodes include P third nodes, and the third nodes are child nodes of the first node.
In a second aspect, an embodiment of the present application provides a signal processing method, including: the second node sends channel parameters to the first node, the channel parameters including channel information
Figure BDA0003298089410000031
And a first parameter comprising noise-related information ≥>
Figure BDA0003298089410000032
Or noise information->
Figure BDA0003298089410000033
The noise-related information->
Figure BDA0003298089410000034
M for indicating the second node corresponds to c Noise correlation between antennas, the noise information ≥>
Figure BDA0003298089410000035
For indicating the noise of the first signal received by the second node, P being an integer greater than 1, M c Is an integer greater than 0.
In one possible embodiment, the channel parameters are compressed matrices
Figure BDA0003298089410000036
Weighted, compression matrix +>
Figure BDA0003298089410000037
Is determined based on the channel parameters.
In one possible embodiment of the method according to the invention,the compression matrix
Figure BDA0003298089410000038
Is L M c Dimension matrix, where L is H c The number of columns.
In one possible embodiment, the compression matrix
Figure BDA0003298089410000039
The following formula is satisfied: />
Figure BDA00032980894100000310
Wherein H c For channel information before compression, R cc Is noise related information before compression.
In one possible embodiment, the first signal is a compressed matrix
Figure BDA00032980894100000311
Weighted, compression matrix +>
Figure BDA00032980894100000312
Is determined based on the channel parameters.
The beneficial effects of the signal processing method provided by the second aspect and each possible implementation manner of the second aspect may refer to the beneficial effects brought by each possible implementation manner of the first aspect, and are not described herein again.
In a third aspect, an embodiment of the present application provides a communication apparatus, including a transceiver unit, configured to acquire channel parameters corresponding to P second nodes, where the channel parameters include channel information
Figure BDA00032980894100000313
And a first parameter comprising noise related information &>
Figure BDA00032980894100000314
Or noise information>
Figure BDA00032980894100000315
The noise-related information->
Figure BDA00032980894100000316
M for indicating the second node corresponds to c Noise correlation between antennas, the noise information ≥>
Figure BDA00032980894100000317
For indicating the noise of the first signal received by the second node, P being an integer greater than 1, M c Is an integer greater than 0; and the processing unit is configured to determine equalization information according to the channel parameters corresponding to the P second nodes, where the equalization information is used to perform channel equalization on a second signal, and the second signal is determined according to first signals received by the P second nodes, respectively.
In a possible implementation, the processing unit is specifically configured to: performing parameter fusion on the channel parameters respectively corresponding to the P second nodes to obtain equivalent parameters; according to the equivalent parameters, equalization information is determined.
In a possible implementation, the processing unit is specifically configured to: channel information corresponding to the P second nodes respectively
Figure BDA00032980894100000318
Performing parameter fusion to obtain equivalent channel information->
Figure BDA00032980894100000319
And noise information corresponding to the P second nodes respectively
Figure BDA00032980894100000320
Performing parameter fusion to obtain equivalent noise information>
Figure BDA00032980894100000321
Or, respectively corresponding noise related information to the P second nodes
Figure BDA00032980894100000322
Performing parameter fusion to obtain equivalent noise related information->
Figure BDA00032980894100000323
/>
In a possible implementation, the processing unit is further configured to: based on the equivalent noise information
Figure BDA00032980894100000324
Determining equivalent noise related information &>
Figure BDA00032980894100000325
In a possible implementation, the processing unit is specifically configured to: channel information corresponding to the P second nodes respectively
Figure BDA00032980894100000326
Summing or matrix splicing to obtain the equivalent channel information &>
Figure BDA00032980894100000327
In a possible implementation, the processing unit is specifically configured to: noise information corresponding to the P second nodes
Figure BDA00032980894100000328
Summing or matrix splicing is carried out to obtain the equivalent noise information->
Figure BDA00032980894100000329
In a possible implementation, the processing unit is specifically configured to: noise-related information corresponding to the P second nodes respectively
Figure BDA00032980894100000330
Summing or matrix splicing is carried out to obtain the equivalent noise related information->
Figure BDA00032980894100000331
In a possible embodiment, the equalization information W H The following formula is satisfied:
Figure BDA00032980894100000332
in one possible embodiment, the channel parameters are compressed matrices
Figure BDA00032980894100000333
Weighted, the compression matrix->
Figure BDA00032980894100000334
Is determined based on the channel parameters.
In one possible embodiment, the compression matrix
Figure BDA0003298089410000041
Is L M c Dimension matrix, wherein L is H c The number of columns.
In one possible embodiment, the compression matrix
Figure BDA0003298089410000042
The following formula is satisfied: />
Figure BDA00032980894100000417
Wherein H c For channel information before compression, R cc Is noise related information before compression.
In a possible implementation, the processing unit is further configured to: and performing signal fusion on the first signals respectively received by the P second nodes to obtain the second signals.
In a possible implementation, the processing unit is specifically configured to: and summing or matrix splicing the first signals respectively received by the P second nodes to obtain the second signals.
In one possible embodiment, the first signal is a compressed matrix
Figure BDA0003298089410000043
Weighted, the compression matrix->
Figure BDA0003298089410000044
Is determined based on the channel parameters.
In one possible embodiment, the P second nodes include the communication device and P-1 third nodes or the P second nodes include P third nodes, which are child nodes of the communication device.
The beneficial effects of the signal processing method provided by the third aspect and each possible implementation manner of the third aspect may refer to the beneficial effects brought by each possible implementation manner of the first aspect, and are not described herein again.
In a fourth aspect, an embodiment of the present application provides a communication apparatus, including: a transceiving unit for transmitting a channel parameter to the first node, the channel parameter including channel information
Figure BDA0003298089410000045
And a first parameter comprising noise-related information ≥>
Figure BDA0003298089410000046
Or noise information->
Figure BDA0003298089410000047
The noise-related information->
Figure BDA0003298089410000048
M for indicating the correspondence of the communication device c Noise correlation between antennas, the noise information ≥>
Figure BDA0003298089410000049
For indicating the noise of a first signal received by the communication device, P being an integer greater than 1, M c Is an integer greater than 0.
In a 1In one possible embodiment, the channel parameters are compressed matrices
Figure BDA00032980894100000410
Weighted, the compression matrix->
Figure BDA00032980894100000411
Is determined based on the channel parameters.
In one possible embodiment, the compression matrix
Figure BDA00032980894100000412
Is L M c Dimension matrix, where L is H c The number of columns.
In one possible embodiment, the compression matrix
Figure BDA00032980894100000413
The following formula is satisfied: />
Figure BDA00032980894100000414
Wherein H c For channel information before compression, R cc Is noise related information before compression.
In one possible embodiment, the first signal is a compressed matrix
Figure BDA00032980894100000415
Weighted, the compression matrix->
Figure BDA00032980894100000416
Is determined based on the channel parameters.
The advantageous effects of the signal processing method provided by the fourth aspect and each possible implementation manner of the fourth aspect may refer to the advantageous effects brought by each possible implementation manner of the first aspect and are not described herein again.
In a fifth aspect, an embodiment of the present application provides a communication apparatus, including: a processor and a memory, the memory being configured to store a computer program, the processor being configured to invoke and execute the computer program stored in the memory to perform a method as in the first aspect, the second aspect or each possible implementation.
In a sixth aspect, an embodiment of the present application provides a chip, including: a processor configured to call and execute the computer instructions from the memory, so that the device on which the chip is installed performs the method according to the first aspect, the second aspect, or any possible implementation manner.
In a seventh aspect, an embodiment of the present application provides a computer-readable storage medium for storing computer program instructions, where the computer program instructions cause a computer to execute the method according to the first aspect, the second aspect, or each possible implementation manner.
In an eighth aspect, embodiments of the present application provide a computer program product, which includes computer program instructions, and the computer program instructions make a computer execute the method according to the first aspect, the second aspect, or each possible implementation manner.
Drawings
Fig. 1 is a schematic architecture diagram of a communication system to which an embodiment of the present application is applied.
FIG. 2 is a schematic diagram of an XL-MIMO scenario as applied to an embodiment of the present application.
Fig. 3 is a schematic diagram of a distributed baseband processing architecture according to the present application.
Fig. 4a is a schematic diagram of a star-type distributed baseband processing architecture according to an embodiment of the present disclosure.
Fig. 4b is a schematic diagram of another star-type distributed baseband processing architecture according to the embodiment of the present application.
Fig. 5 is a schematic flow chart of a signal processing method 500 provided in an embodiment of the present application.
Fig. 6 is a schematic flowchart of a method for determining equalization information according to an embodiment of the present application.
Fig. 7 is a schematic flowchart of another method for determining equalization information according to an embodiment of the present application.
Fig. 8 is a schematic structural diagram of a communication device 600 according to an embodiment of the present disclosure.
Fig. 9 is another schematic block diagram of a communication device 700 according to an embodiment of the present disclosure.
Detailed Description
The technical solution in the present application will be described below with reference to the accompanying drawings.
The antenna detection method provided by the application can be applied to various communication systems, such as: long Term Evolution (LTE) system, LTE FreQuency Division DuPlex (FDD) system, LTE Time Division DuPlex (TDD) system, universal Mobile Telecommunications System (UMTS) system, UMTS), worldwide InteroPerability for Microwave Access (WiMAX) communication system, future fifth generation (5G) mobile communication system or new radio access technology (NR) and enhanced mobile bandwidth for 5G mobile communication system, ultra-reliable low-latency communication (ultra-reliable low-latency communication, urrllc), and mass machine tyPe communications (mtc), device-to-device (D2D) communication systems, satellite communication systems, internet of things (IoT), narrowband internet of things (NB-IoT) systems, global system for mobile communications (GSM), enhanced data rate GSM Evolution (EDGE for GSM Evolution), wideband Code Division MultiPle Access (WCDMA) systems, code division multiPle access (code division multiPle access, CDMA 2000) systems, time division-synchronous code division multiPle access (TD-SCDMA) systems. The 5G mobile communication system may include a non-independent Network (NSA) and/or an independent network (SA), among others.
The antenna detection method provided by the application can also be applied to future communication systems, such as a sixth generation mobile communication system and the like. This is not a limitation of the present application.
Fig. 1 is a schematic architecture diagram of a communication system to which an embodiment of the present application is applied. As shown in fig. 1, the mobile communication system includes a core network device 110, a network device 120, and at least one terminal device (e.g., a terminal device 130 and a terminal device 140 in fig. 1). The terminal equipment is connected with the network equipment in a wireless mode, and the network equipment is connected with the core network equipment in a wireless or wired mode. The core network device and the network device may be separate physical devices, or the function of the core network device and the logic function of the network device may be integrated on the same physical device, or a physical device may be integrated with a part of the function of the core network device and a part of the function of the network device. The terminal equipment may be fixed or mobile. Fig. 1 is a schematic diagram, and other network devices, such as a wireless relay device and a wireless backhaul device, may also be included in the communication system, which are not shown in fig. 1. The embodiments of the present application do not limit the number of core network devices, and terminal devices included in the mobile communication system.
The network device is an access device in which the terminal device is accessed to the mobile communication system in a wireless manner, and may be a base station NodeB, an evolved node b, a base station in an NR mobile communication system, a base station in a future mobile communication system, or an access node in a WiFi system, and the like.
The Terminal device may also be referred to as a Terminal, a User EQuiPment (UE), a Mobile Station (MS), a Mobile Terminal (MT), and the like. The terminal device may be a mobile Phone (mobile Phone), a tablet computer (Pad), a computer with a wireless transceiving function, a Virtual Reality (VR) terminal device, an Augmented Reality (AR) terminal device, a wireless terminal in industrial control (industrial control), a wireless terminal in self driving (self driving), a wireless terminal in remote surgery (remote medical supply), a wireless terminal in smart grid (smart grid), a wireless terminal in transPortation safety (transPortation safety), a wireless terminal in smart city (smart city), a wireless terminal in smart home (smart home), and so on.
The network equipment and the terminal equipment can be deployed on the land, including indoors or outdoors, handheld or vehicle-mounted; can also be deployed on the water surface; it may also be deployed on airborne airplanes, balloons, and satellites. The embodiment of the application does not limit the application scenarios of the network device and the terminal device.
The communication between the network device and the terminal device and between the terminal device and the terminal device may be performed through a licensed sPectrum (licensed sPectrum), may be performed through an unlicensed sPectrum (unlicensed sPectrum), and may also be performed through both the licensed sPectrum and the unlicensed sPectrum. The network device and the terminal device may communicate with each other via a 6G or less spectrum, may communicate via a 6G or more spectrum, and may communicate using both a 6G or less spectrum and a 6G or more spectrum. The embodiment of the application does not limit the spectrum resources used between the network device and the terminal device.
It should be understood that the present application is not limited to the specific form of the network device and the terminal device.
In the communication system, a multiple-in-multiple-out (MIMO) technology and an extra-large-scale multiple-input-multiple-output (XL-MIMO) technology are used as core technologies of a future mobile communication system, so that the spectrum efficiency and the energy efficiency of the mobile communication system can be greatly improved. As shown in fig. 2, the network device 210 (for example, the network device 120 in fig. 1) performs transmission of uplink information and/or downlink information with a plurality of terminal devices 220 (for example, the terminal devices 130 and 140 in fig. 1) through a plurality of antennas or antenna arrays, where any terminal device may be provided with a plurality of antennas or antenna arrays (not shown in the figure) for sending the uplink information to the network device 210 or receiving the downlink information sent by the network device 210. The channel equalization technique, such as Maximum Ratio Combining (MRC), zero Forcing (ZF), minimum Mean Square Error (MMSE), etc., can reduce crosstalk (referred to as inter-stream crosstalk) between user data streams of an uplink transmission link to ensure the receiving performance of a base station, and is a key technique for realizing high spectral efficiency and energy efficiency of the XL-MIMO technique.
In MIMO or XL-MIMO scene, a plurality of terminal devices are considered to send signals to network devices equipped with M antennas or antenna sub-arrays, and in an uplink transmission link, a channel matrix between the network device and the plurality of terminal devices is
Figure BDA0003298089410000061
Figure BDA0003298089410000062
Represents an M by K dimensional matrix with each element in the matrix being a complex number, or a value greater than or equal to>
Figure BDA0003298089410000063
Represents a user data stream signal, <' > or>
Figure BDA0003298089410000064
Representing interference and noise of the network device, where K is the number of user data streams of the plurality of terminal devices, and the network device receives the signal ≥ and>
Figure BDA0003298089410000065
satisfies the following formula (1):
y＝Hs+n (1)
on the basis of the above uplink transmission link model, the MMSE equalization algorithm can be implemented under the white noise assumption, or can be implemented under the colored noise assumption. For example, the MMSE equalization algorithm under independent white gaussian noise is implemented by the following equation (2):
W H ＝(H H H+σ 2 I) -1 H H (2)
wherein σ 2 For the average power of white noise, I is the identity matrix and the subscript H is the conjugate transpose, e.g. H H Is the conjugate transpose of H.
The difference between the actual noise and the white noise of the signal received by the network device is large, and the above formula (2) does not consider that there is an obvious correlation between different antenna noises, so that the above formula (2) is not obviously improved in comparison with ZF equalization in practical application. The equalization algorithm takes into account the information about the correlation of the antenna reception noise for more efficient interference cancellation, i.e. taking into account the colored noise assumption. For example, the MMSE equalization algorithm under colored noise is implemented by the following equation (3):
W H ＝(H H R -1 H+I) -1 H H R -1 (3)
wherein R is noise related information for indicating the noise correlation of a plurality of antenna holders. The MMSE equalization algorithm under colored noise can effectively reduce the crosstalk between uplink streams. However, as the number of antennas of the network device increases, the network device performs centralized channel equalization for each antenna or antenna sub-array, so that the amount of data to be exchanged is large and the computational complexity is high.
Fig. 3 is a schematic diagram of a distributed baseband processing architecture according to the present application. In fig. 3, each distributed baseband processing unit, for example, the distributed baseband processing units 311, 312, and 313, respectively receive signaling and/or data sent by the terminal device through a corresponding antenna cluster (for example, one of the antenna cluster 1 to the antenna cluster P), for example, the distributed baseband processing unit is connected to a radio frequency (RE) unit in the antenna cluster, each distributed baseband processing unit determines an own equalization matrix according to the received signaling and/or data, and sends the obtained equalization matrix to the next distributed baseband processing unit, the next distributed baseband processing unit corrects the own generated equalization matrix according to the received equalization matrix, and then sends the corrected equalization matrix to the next distributed baseband processing unit, and so on, after multiple rounds of iteration, a converged equalization matrix is obtained, and further, channel equalization processing is performed. Therefore, in the existing distributed equalization technology, for the MMSE equalization algorithm based on the white noise, through each distributed baseband processing unit in the network device, multiple rounds of iteration are realized through data interaction among each distributed baseband processing unit to achieve the equalization effect of the centralized equalization algorithm.
In order to solve the above technical problem, in the process of performing distributed channel equalization by a network device according to the embodiment of the present application, on one hand, a "central node (a first node in the following text)" is introduced on the basis of a plurality of distributed nodes (for example, the distributed baseband processing unit), so that the plurality of nodes all send interactive data to the central node, and the central node combines the interactive data of each node to determine equalization information, thereby performing channel equalization; on the other hand, noise-related information or noise information is included in the interactive data, and information on the antenna reception noise correlation of colored noise is represented by the noise-related information or noise information. The equalization algorithm based on the colored noise can more effectively eliminate the interference, so that the embodiment of the application can realize channel equalization by using a star-shaped distributed baseband processing framework and the equalization algorithm based on the colored noise, can realize the equalization effect of a centralized equalization algorithm without iteration, and reduces the interactive data volume and the calculation complexity.
For the purpose of understanding the embodiments of the present application, the terms used in the embodiments of the present application will be described first.
1. Channel equalization: the method refers to equalization of channel characteristics, that is, an equalizer at a receiving end generates characteristics opposite to those of a channel, and is used for counteracting inter-stream interference introduced by a wireless channel.
2. Dimension Reduction (DR): in a very large scale communication system, the dimensionality of high dimensional data is reduced (compressed) by linear or nonlinear transformation, the purposes of reducing communication traffic and calculating complexity are achieved, and meanwhile, compression cannot generate overhigh information loss as far as possible.
The following describes a signal processing method provided in an embodiment of the present application with reference to the drawings.
The embodiment of the present application may be applied to an uplink transmission process, where an execution subject is a receiving end in the uplink transmission process, that is, a network device, for example, the network device 120 in fig. 1. It should be understood that, for ease of understanding and explanation, the method provided in the embodiment of the present application is mainly described by taking an interaction between a first node and P (P is an integer greater than 1) second nodes of a network device as an example. In one scenario, the first node may be, for example, the node 401 in fig. 4a as a central node, the second nodes are nodes respectively connected to the antenna clusters in fig. 4a, each second node may acquire signals received by the corresponding antenna cluster and process the received signals, for example, the second nodes include the first node 401 and other non-central nodes 402, and the non-central nodes except the first node in each second node are all connected to the first node in a wired or wireless manner, in which case, each second node including the first node may be the distributed baseband processing unit and is deployed in a baseband down shift (BBL), and the first node and the baseband up shift (BBH) may be connected in a wired or wireless manner. In another scenario, the first node as a central node may be, for example, the node 411 in fig. 4b, the second nodes are non-central nodes, such as the node 412 in fig. 4b, each of the second nodes is connected to the first node in a wired or wireless manner, in this case, the first node may be a BBH or a processing unit disposed in the BBH, the second nodes may be disposed in a BBL, and the second nodes may be, for example, the above-mentioned distributed baseband processing units.
It should be understood that each second node corresponds to one antenna cluster respectively, and is used for performing signal processing on uplink signals (including signaling and/or data) received on the antenna cluster.
It should be noted that the child nodes of the first node are also referred to as third nodes hereinafter, that is, the P second nodes include the first node and P-1 third nodes (see fig. 4 a), or the P second nodes include P third nodes (see fig. 4 b).
Fig. 5 is a schematic flow chart of a signal processing method 500 provided in an embodiment of the present application. As shown in fig. 5, the method 500 may include S510 and S520. The various steps in method 500 are described below.
S510, the second node sends channel parameters to the first node, and the channel parameters comprise channel information
Figure BDA0003298089410000081
And a first parameter comprising noise related information &>
Figure BDA0003298089410000082
Or noise information>
Figure BDA0003298089410000083
The noise-related information->
Figure BDA0003298089410000084
M for indicating correspondence of second node c Noise correlation between individual antennas, the noise information &>
Figure BDA0003298089410000085
For indicating noise of a first signal received by a second node, P being an integer greater than 1, M c Is an integer greater than 0.
Correspondingly, the first node acquires channel parameters corresponding to the P second nodes respectively. It should be noted that, in the scenario shown in fig. 4a, the first node receives channel parameters respectively sent by P-1 third nodes in P second nodes, and reads the channel parameters obtained by the first node itself; in the scenario shown in fig. 4b, the first node receives the channel parameters respectively transmitted by the P second nodes. The first node serving as one of the second nodes to obtain its own channel parameter can be understood by those skilled in the art, and is not described in detail in this embodiment. For the sake of simplicity, the following description will only take the first node receiving the channel parameters respectively transmitted by the P second nodes as an example.
And S520, the first node determines equalization information according to the channel parameters corresponding to the P second nodes respectively, wherein the equalization information is used for performing channel equalization on a second signal, and the second signal is determined according to the first signal received by the P second nodes respectively.
It should be noted that the channel parameters sent by the second node at least include channel information
Figure BDA0003298089410000086
And noise related information
Figure BDA0003298089410000087
Or at least comprises channel information->
Figure BDA0003298089410000088
And noise information->
Figure BDA0003298089410000089
Alternatively to this, the first and second parts may,
Figure BDA00032980894100000810
is L by L dimension matrix, and>
Figure BDA00032980894100000811
is L by L dimension matrix, and>
Figure BDA00032980894100000812
is an L by N dimensional matrix. Where N is related to the number of pilot signals in a time unit and the subcarrier granularity, e.g. counted once every 48 subcarriers in a time slot>
Figure BDA00032980894100000813
Each time a calculation is made based on 2 pilot symbols, N =48 × 2.
In some embodiments, the channel parameters transmitted by the second node further comprise the first signal. It should be understood that the first signal may be the antenna cluster c through which the second node corresponds (the antenna cluster c may include M as described above) c Antennas) of the received uplink signal.
The first parameter includes noise information
Figure BDA00032980894100000814
Then, the first node may ≥ according to the respective noise information ≥ from the P second nodes>
Figure BDA00032980894100000815
Determining noise-related information pick>
Figure BDA00032980894100000816
Noise information
Figure BDA00032980894100000817
Can embody M c Noise correlation between the antennas.
In the above S520, since the channel parameters respectively corresponding to the P second nodes all carry the information capable of embodying M c And the first node realizes an equalization algorithm based on colored noise based on equalization information determined by the channel parameters respectively corresponding to the P second nodes.
The equalization information may be, for example, an equalization matrix, such as the equalization matrix determined by the foregoing equation (3).
Illustratively, channel information
Figure BDA0003298089410000091
And the first parameter can be M corresponding to the second node through the second node c The antenna receives the pilot signal sent by the terminal equipment and obtains the pilot signal through measurement. Alternatively, the second node may send channel information ≧ to the first node every time unit>
Figure BDA0003298089410000092
And a first parameter, and/or the first node may acquire its own channel information ≧ at each time unit>
Figure BDA0003298089410000093
And a first parameter. It can be appreciated that the channel information of the first node itself ≥ s>
Figure BDA0003298089410000094
And the first parameter is M corresponding to the first node through the first node c The antenna receives the pilot signal sent by the terminal equipment and measures the pilot signal. Wherein, the time unit may be a slot, a subframe, etc.
It is understood that each of the secondThe number of the antennas or antenna sub-arrays corresponding to the two nodes may be the same or different, and this is not limited in this application. It should also be understood that M c The antennas are divided into an example by antenna granularity, but do not represent any limitation to the present application, and for example, the antennas may be divided into antenna sub-array granularity, that is, M c The antenna can be replaced by M c And (4) antenna sub-arrays.
S520 will be described with reference to fig. 6 and 7.
As shown in fig. 6, the S520 may specifically include the following S521 and S522:
s521, the first node performs parameter fusion on the channel parameters respectively corresponding to the P second nodes to obtain equivalent parameters;
and S522, the first node determines the balance information according to the equivalent parameters.
In S521, the first node may perform parameter fusion on each channel parameter to obtain an equivalent parameter of each channel parameter. For example, as shown in fig. 7, the first node may respectively correspond to the channel information of the P second nodes
Figure BDA0003298089410000095
Performing parameter fusion to obtain equivalent channel information->
Figure BDA0003298089410000096
Moreover, the first node may perform parameter fusion on the first parameters corresponding to the P second nodes, for example, S5211-1 in fig. 7, and the first node performs parameter fusion on the noise information corresponding to the P second nodes, respectively
Figure BDA0003298089410000097
Performing parameter fusion to obtain equivalent noise information->
Figure BDA0003298089410000098
Or as in S5211-2 of fig. 7, the first node may determine the noise-related information ≥ corresponding to the P second nodes respectively>
Figure BDA0003298089410000099
Performing parameter fusion to obtain equivalent noise related information->
Figure BDA00032980894100000910
Aiming at the channel information corresponding to the P second nodes respectively in the S5211-1 and S5211-2
Figure BDA00032980894100000911
Performing parameter fusion to obtain equivalent channel information->
Figure BDA00032980894100000926
Channel information &'s corresponding to P second nodes can be specifically combined by the first node>
Figure BDA00032980894100000912
Summing or matrix splicing is carried out to obtain the equivalent channel information->
Figure BDA00032980894100000913
For example, in a summing strategy, equivalent channel information ≧ is>
Figure BDA00032980894100000914
In the matrix splicing strategy, equivalent information ≥ is>
Figure BDA00032980894100000915
For the noise information corresponding to the P second nodes in the above S5211-1, the first node respectively
Figure BDA00032980894100000916
Performing parameter fusion to obtain equivalent noise information->
Figure BDA00032980894100000917
Specifically, the noise information ≥ corresponding to the P second nodes can be determined by the first node>
Figure BDA00032980894100000918
Summing or matrix splicing is carried out to obtain equivalent noise information->
Figure BDA00032980894100000919
For example, in a summation strategy, equivalent noise information
Figure BDA00032980894100000920
Equivalent noise information &inmatrix stitching strategy>
Figure BDA00032980894100000921
For the noise-related information corresponding to the P second nodes in S5211-2 above, the first node respectively corresponds to the P second nodes
Figure BDA00032980894100000922
Performing parameter fusion to obtain equivalent noise related information->
Figure BDA00032980894100000923
Specifically, the noise-related information ≥ corresponding to the P second nodes can be determined by the first node>
Figure BDA00032980894100000924
Summing or matrix splicing is carried out to obtain equivalent noise related information->
Figure BDA00032980894100000925
For example, in a summing strategy, equivalent noise-related information ≥ is>
Figure BDA0003298089410000101
In a matrix splicing strategy, pairs->
Figure BDA0003298089410000102
Performing block diagonalization matrix splicing to obtain->
Figure BDA0003298089410000103
It can be understood that the channel parameter obtained by the first node through the summation strategy is lower in complexity of a processing process for subsequently determining the equalization information than the channel parameter obtained through the matrix splicing strategy, and the channel parameter obtained by the first node through the matrix splicing strategy is higher in performance of the subsequently determined equalization information than the channel parameter obtained through the summation strategy.
If the first node performs S5211-1 as shown in fig. 7, it is necessary to further determine equivalent noise related information according to the equivalent noise information, i.e., S5212 in fig. 7. Illustratively, the equivalent noise information may satisfy the following formula:
Figure BDA0003298089410000104
in the above S522, the first node determines the equalization information W according to the equivalent parameter H This can be achieved, for example, by the following formula:
Figure BDA0003298089410000105
in some embodiments, to further reduce the amount of data exchanged, the channel parameters and/or the first signal transmitted by the second node to the first node are compressed matrices
Figure BDA0003298089410000106
Weighted, i.e. compressed, channel parameters.
Optionally, the compression matrix
Figure BDA0003298089410000107
Is determined based on the channel parameters. Compression matrix->
Figure BDA0003298089410000108
May be L M c Dimension matrix, wherein L ≧ rank (H) c ) Note that rank (H) c ) I.e. the channel information H c I.e. the number of user data streams received by the second node, when L is greater than or equal to the channel numberMessage H c Can lossless compress the channel parameters and/or the first signal when L is less than the channel information H c Is easy to cause signal loss, so when L is equal to the channel information H c The maximum lossless compression is performed when the number of columns is equal to the maximum; m c The number of the antennas corresponding to any second node.
For example, a compression matrix
Figure BDA0003298089410000109
The following formula is satisfied:
Figure BDA00032980894100001010
wherein H c For channel information before compression, H c Is M c Multiplication by L-dimensional matrix, R cc For noise-related information before compression, R cc Is M c Multiplying by M c A dimension matrix.
Illustratively, the second node passes
Figure BDA00032980894100001011
The weighting of the channel parameters and/or the first signal may be: for channel information H c Weighting to obtain compressed channel information->
Figure BDA00032980894100001012
For noise related information R cc Weighting to compressed noise related information &>
Figure BDA00032980894100001013
For noise information n c Weighting to compressed noise information->
Figure BDA00032980894100001014
For the first signal y c Weighted to obtain the compressed first signal->
Figure BDA00032980894100001015
It will be appreciated that in compressing the matrix
Figure BDA00032980894100001016
In the case of an identity matrix, the compressed channel parameters are identical to the channel parameters before compression, i.e. </>>
Figure BDA00032980894100001017
And H c Is equal to or greater than>
Figure BDA00032980894100001018
And R cc Is equal to or greater than>
Figure BDA00032980894100001019
And n c The same is true. In other words, channel information, noise-related information
Figure BDA00032980894100001020
Noise information->
Figure BDA00032980894100001021
May all be compressed or at least one of the three may be uncompressed.
Exemplarily, before S520, the method may further include: the first node determines second signals according to the first signals respectively received by the P second nodes. The first signal may be, for example, the first signal compressed by the compression matrix. For example, the first node may perform signal fusion on the first signals respectively received by the P second nodes to obtain the second signals. The signal fusion process may be, for example, a process in which the first node sums or matrix splices the first signals respectively received by the P second nodes. For example, in a summation strategy, the second signal
Figure BDA0003298089410000111
In the matrix splicing strategy, the second signal->
Figure BDA0003298089410000112
Further, the first node may perform equalization processing on the second signal according to the equalization matrix to obtain an estimate of the signal sent by the terminal device. For example, the estimation result of the terminal device transmission signal may satisfy the formula:
Figure BDA0003298089410000113
that is to say
Figure BDA0003298089410000114
Figure BDA0003298089410000115
/>
The channel parameters transmitted in this embodiment are channel parameters subjected to dimension compression DR, and on this basis, the algorithm adopted in the equalization process provided in this embodiment may be referred to as a DRMMSE equalization algorithm, but this does not limit the present application, and this embodiment does not limit the nomenclature of the algorithm adopted in the equalization process.
In one possible implementation, a practical embodiment employs a typical M-based distributed star-based baseband processing architecture c =128 antenna base station, the base station antennas are divided into P =8 antenna clusters, the base station serves at most L =16 single-antenna users at the same time, and a 16-QAM coding modulation scheme is considered.
Therefore, in the embodiment of the present application, the channel parameters respectively corresponding to the P second nodes acquired by the first node carry information related to noise between the Mc antennas, and the first node determines the equalization information based on the channel parameters and performs channel equalization according to the equalization information, thereby implementing distributed equalization processing based on colored noise, and reducing the amount of data exchanged between nodes and the computational complexity of the first node.
The method provided by the embodiment of the present application is described in detail above with reference to fig. 5 to 7. Hereinafter, the apparatus provided in the embodiment of the present application will be described in detail with reference to fig. 8 and 9.
Fig. 8 is a schematic structural diagram of a communication device 600 according to an embodiment of the present disclosure. As shown in fig. 8, the communication device 600 may include a transceiving unit 610 and a processing unit 620.
Optionally, the communication apparatus 600 may be applied to the first node in the above method embodiments, and may be, for example, a component (e.g., a chip or a system of chips, etc.) in a network device.
When the communication apparatus 600 is applied to a first node, the transceiver unit 610 may be configured to acquire channel parameters corresponding to P second nodes, where the channel parameters include channel information
Figure BDA0003298089410000116
And a first parameter comprising noise-related information ≥>
Figure BDA0003298089410000117
Or noise information->
Figure BDA0003298089410000118
The noise-related information->
Figure BDA0003298089410000119
M for indicating the second node corresponds to c Noise correlation between individual antennas, the noise information &>
Figure BDA00032980894100001110
For indicating the noise of the first signal received by the second node, P being an integer greater than 1, M c Is an integer greater than 0; the processing unit 620 may be configured to determine, according to the channel parameters corresponding to the P second nodes, equalization information used to perform channel equalization on a second signal, where the second signal is determined according to the first signals received by the P second nodes, respectively.
In some embodiments, the processing unit 620 is specifically configured to:
performing parameter fusion on the channel parameters respectively corresponding to the P second nodes to obtain equivalent parameters;
based on the equivalent parameters, equalization information is determined.
In some embodiments, the processing unit 620 is specifically configured to:
channel information corresponding to the P second nodes respectively
Figure BDA00032980894100001111
Performing parameter fusion to obtain equivalent channel information->
Figure BDA00032980894100001112
And (c) and (d),
noise information corresponding to the P second nodes respectively
Figure BDA00032980894100001113
Performing parameter fusion to obtain equivalent noise information>
Figure BDA00032980894100001114
Or the first node combines the noise-related information corresponding to the P second nodes with the noise-related information->
Figure BDA00032980894100001115
Performing parameter fusion to obtain equivalent noise related information->
Figure BDA00032980894100001116
In some embodiments, the processing unit 620 is further configured to:
based on the equivalent noise information
Figure BDA00032980894100001117
Determining equivalent noise-related information ≥>
Figure BDA00032980894100001118
In some embodiments, the processing unit 620 is specifically configured to:
channel information corresponding to the P second nodes respectively
Figure BDA0003298089410000121
Summing or matrix splicing is carried out to obtain the equivalent channel information->
Figure BDA0003298089410000122
/>
In some embodiments, the processing unit 620 is specifically configured to:
noise information corresponding to the P second nodes
Figure BDA0003298089410000123
Summing or matrix splicing is carried out to obtain the equivalent noise information->
Figure BDA0003298089410000124
In some embodiments, the processing unit 620 is specifically configured to:
noise-related information corresponding to the P second nodes respectively
Figure BDA0003298089410000125
Summing or matrix splicing to obtain the equivalent noise-related information->
Figure BDA0003298089410000126
In some embodiments, the equalization information W H The following formula is satisfied:
Figure BDA0003298089410000127
in some embodiments, the channel parameters are compressed matrices
Figure BDA0003298089410000128
Weighted, compression matrix +>
Figure BDA0003298089410000129
Is determined based on the channel parameters.
In some embodiments, the compression matrix
Figure BDA00032980894100001210
Is L M c Dimension matrix, wherein L is H c The number of columns.
In some embodiments, the compression matrix
Figure BDA00032980894100001211
The following formula is satisfied:
Figure BDA00032980894100001212
in some embodiments, the processing unit 620 is further configured to:
and performing signal fusion on the first signals respectively received by the P second nodes to obtain the second signals.
In some embodiments, the processing unit 620 is specifically configured to:
and summing or matrix splicing the first signals respectively received by the P second nodes to obtain the second signals.
In some embodiments, the first signal is a compressed matrix
Figure BDA00032980894100001213
Weighted, the compression matrix->
Figure BDA00032980894100001214
Is determined based on the channel parameters.
In some embodiments, the P second nodes include a first node and P-1 third nodes or the P second nodes include P third nodes, the third nodes being child nodes of the first node.
It should be understood that the specific processes of the units for executing the corresponding steps are already described in detail in the above method embodiments, and therefore, for brevity, detailed descriptions thereof are omitted.
When the communication device 600 is a first node, the processing unit 620 in the communication device 600 may be implemented by a processor, for example, may correspond to the processor 710 in the communication device 700 shown in fig. 9. The transceiving unit 610 may be implemented by a transceiver, which may correspond to the transceiver 720 in the communication device 700 shown in fig. 9, for example.
When the communication apparatus 600 is a chip or a system of chips configured in a network device, the processing unit 620 and the transceiver unit 610 in the communication apparatus 600 may be implemented by an input/output interface, a circuit, or the like.
Alternatively, the communication apparatus 600 may be applied to the second node in the above method embodiments, and may be, for example, a component (e.g., a chip or a system of chips, etc.) configured in a network device.
When the communication apparatus 600 is applied to a second node, the transceiving unit 610 may be configured to transmit a channel parameter to the first node, where the channel parameter includes channel information
Figure BDA00032980894100001215
And a first parameter comprising noise-related information ≥>
Figure BDA00032980894100001216
Or noise information->
Figure BDA00032980894100001217
The noise related information>
Figure BDA00032980894100001218
M for indicating the second node corresponds to c Noise correlation between individual antennas, the noise information &>
Figure BDA00032980894100001219
For indicating the noise of the first signal received by the second node, P being an integer greater than 1, M c Is an integer greater than 0.
In some embodiments, the channel parameters are compressed matrices
Figure BDA00032980894100001220
Weighted, the compression matrix->
Figure BDA00032980894100001221
Is determined based on the channel parameters. />
In some embodiments, the compression matrix
Figure BDA00032980894100001222
Is L x M c Dimension matrix, where L is H c The number of columns.
In some embodiments, the compression matrix
Figure BDA0003298089410000131
The following formula is satisfied:
Figure BDA0003298089410000132
in some embodiments, the first signal is a compressed matrix
Figure BDA0003298089410000133
Weighted, compression matrix +>
Figure BDA0003298089410000134
Is determined based on the channel parameters.
In some embodiments, the equalization information W H The following formula is satisfied:
Figure BDA0003298089410000135
it should be understood that, the specific processes of the units for executing the corresponding steps are already described in detail in the above method embodiments, and are not described herein again for brevity.
When the communication device 600 is a second node, the processing unit 620 in the communication device 600 may be implemented by a processor, for example, may correspond to the processor 710 in the communication device 700 shown in fig. 9. The transceiving unit 610 may be implemented by a transceiver, which may for example correspond to the transceiver 720 in the communication device 700 shown in fig. 9.
When the communication apparatus 600 is a chip or a system of chips configured in a network device, the processing unit 620 and the transceiver unit 610 in the communication apparatus 600 may be implemented by an input/output interface, a circuit, and the like.
Fig. 9 is another schematic block diagram of a communication device 700 according to an embodiment of the present disclosure. As shown in fig. 7, the apparatus 700 may include: a processor 710, a transceiver 720, and a memory 730. The processor 710, the transceiver 720 and the memory 730 are in communication with each other through an internal connection path, the memory 730 is used for storing instructions, and the processor 710 is used for executing the instructions stored in the memory 730 to control the transceiver 720 to transmit and/or receive signals.
It should be understood that the communication device 700 may correspond to the first node in the above method embodiments, and may be configured to perform various steps and/or procedures performed by the first node in the above method embodiments. Alternatively, the memory 730 may include both read-only memory and random access memory and provides instructions and data to the processor. The portion of memory may also include non-volatile random access memory. Memory 730 may be a separate device or may be integrated into processor 710. The processor 710 may be configured to execute the instructions stored in the memory 730, and when the processor 710 executes the instructions stored in the memory, the processor 710 is configured to perform the steps and/or processes of the method embodiment corresponding to the first node described above.
Optionally, the communication device 700 is the first node in the previous embodiments.
Optionally, the communication device 700 is the second node in the previous embodiments.
The transceiver 720 may include a transmitter and a receiver, among other things. The transceiver 720 may further include antennas, which may be one or more in number. The processor 710 and the memory 730 may be devices integrated on different chips than the transceiver 720. For example, the processor 710 and the memory 730 may be integrated in a baseband chip, and the transceiver 720 may be integrated in a radio frequency chip. The processor 710 and the memory 730 may also be integrated on the same chip as the transceiver 720. This is not a limitation of the present application.
Optionally, the communication apparatus 700 is a component configured in a network device, such as a chip, a chip system, or the like.
The transceiver 720 may also be a communication interface, such as an input/output interface, a circuit, etc. The transceiver 720 may be integrated with the processor 710 and the memory 730 on the same chip, such as a baseband chip.
The present application further provides a processing apparatus comprising at least one processor configured to execute a computer program stored in a memory, so as to cause the processing apparatus to perform the method performed by the first node or the second node in the above method embodiments.
The embodiment of the application also provides a processing device which comprises a processor and an input/output interface. The input-output interface is coupled with the processor. The input and output interface is used for inputting and/or outputting information. The information includes at least one of instructions and data. The processor is configured to execute a computer program to cause the processing device to perform the method performed by the first node or the second node in the above method embodiments.
An embodiment of the present application further provides a processing apparatus, which includes a processor and a memory. The memory is used for storing a computer program, and the processor is used for calling and running the computer program from the memory so as to enable the processing device to execute the method executed by the first node or the second node in the method embodiment.
It is to be understood that the processing means described above may be one or more chips. For example, the processing device may be a Field Programmable Gate Array (FPGA), an Application Specific Integrated Circuit (ASIC), a system on chip (SoC), a Central Processing Unit (CPU), a Network Processor (NP), a digital signal processing circuit (DSP), a Microcontroller (MCU), a Programmable Logic Device (PLD), or other integrated chips.
In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in a processor or instructions in the form of software. The steps of the method disclosed in connection with the embodiments of the present application may be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules in a processor. The software modules may be located in ram, flash, rom, prom, or eprom, registers, etc. as is well known in the art. The storage medium is located in a memory, and a processor reads information in the memory and completes the steps of the method in combination with hardware of the processor. To avoid repetition, it is not described in detail here.
It will be appreciated that the memory in the embodiments of the subject application can be either volatile memory or nonvolatile memory, or can include both volatile and nonvolatile memory. The non-volatile memory may be a read-only memory (ROM), a Programmable ROM (PROM), an Erasable PROM (EPROM), an electrically Erasable EPROM (EEPROM), or a flash memory. Volatile memory can be Random Access Memory (RAM), which acts as external cache memory. By way of example, but not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), synchronous Dynamic Random Access Memory (SDRAM), double data rate SDRAM, enhanced SDRAM, SLDRAM, synchronous Link DRAM (SLDRAM), and direct rambus RAM (DR RAM). It should be noted that the memory of the systems and methods described herein is intended to comprise, without being limited to, these and any other suitable types of memory.
According to the method provided by the embodiment of the present application, the present application further provides a computer program product, which includes: computer program code which, when run on a computer, causes the computer to perform the method performed by the first node or the second node in the above-described method embodiments.
According to the method provided by the embodiment of the present application, the present application further provides a computer-readable storage medium storing program code, which, when run on a computer, causes the computer to execute the method performed by the first node and the second node in the above method embodiment.
According to the method provided by the embodiment of the present application, the present application further provides a communication system, where the communication system may include the foregoing terminal device or network device.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
The functions may be stored in a computer-readable storage medium if they are implemented in the form of software functional units and sold or used as separate products. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a read-only memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present application, and shall be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims (44)

1. A method of processing a signal, comprising:
a first node acquires channel parameters corresponding to P second nodes respectively, wherein the channel parameters comprise channel information
Figure FDA0003298089400000011
And a first parameter comprising noise-related information ≥>
Figure FDA0003298089400000012
Or noise information->
Figure FDA0003298089400000013
The noise-related information->
Figure FDA0003298089400000014
M for indicating the second node corresponds to c Noise correlation between antennas, the noise information ≥>
Figure FDA0003298089400000015
For indicating the noise of a first signal received by said second node, P being an integer greater than 1, M c Is an integer greater than 0;
and the first node determines equalization information according to the channel parameters corresponding to the P second nodes respectively, wherein the equalization information is used for performing channel equalization on second signals, and the second signals are determined according to the first signals received by the P second nodes respectively.
2. The method of claim 1, wherein the channel parameter is a compressed matrix
Figure FDA0003298089400000016
Weighted, the compression matrix->
Figure FDA0003298089400000017
Is determined based on the channel parameters.
3. The method of claim 2, wherein the compression matrix is a compressed matrix
Figure FDA0003298089400000018
Is L M c Dimension matrix, wherein L is H c The number of columns.
4. A method according to claim 2 or 3, wherein the compression matrix is
Figure FDA0003298089400000019
The following formula is satisfied:
Figure FDA00032980894000000110
wherein H c For channel information before compression, R cc Is noise related information before compression.
5. The method according to any one of claims 1 to 4, wherein the determining, by the first node, equalization information according to the channel parameters corresponding to the P second nodes, respectively, includes:
the first node performs parameter fusion on the channel parameters respectively corresponding to the P second nodes to obtain equivalent parameters;
and the first node determines the balance information according to the equivalent parameters.
6. The method according to claim 5, wherein the parameter fusion of the channel parameters respectively corresponding to the P second nodes by the first node to obtain equivalent parameters includes:
the first node respectively corresponds to the channel information of the P second nodes
Figure FDA00032980894000000111
Performing parameter fusion to obtain equivalent channel information->
Figure FDA00032980894000000112
And the combination of (a) and (b),
the first node respectively corresponds noise information of the P second nodes
Figure FDA00032980894000000113
Performing parameter fusion to obtain equivalent noise information->
Figure FDA00032980894000000114
Or the first node respectively makes the noise related information corresponding to the P second nodes->
Figure FDA00032980894000000115
Performing parameter fusion to obtain equivalent noise related information->
Figure FDA00032980894000000116
7. The method of claim 6, further comprising:
the first node according to the equivalent noise information
Figure FDA00032980894000000129
Determining equivalent noise-related information ≥>
Figure FDA00032980894000000117
8. The method according to claim 6 or 7, wherein the first node respectively corresponds to the P second nodes with channel information
Figure FDA00032980894000000118
Performing parameter fusion to obtain equivalent channel information->
Figure FDA00032980894000000119
The method comprises the following steps:
the first node respectively corresponds to the channel information of the P second nodes
Figure FDA00032980894000000120
Summing or matrix splicing is carried out to obtain the equivalent channel information->
Figure FDA00032980894000000121
9. The method according to claim 6 or 7, wherein the first node corresponds noise information to the P second nodes respectively
Figure FDA00032980894000000122
Performing parameter fusion to obtain equivalent noise information->
Figure FDA00032980894000000123
The method comprises the following steps: />
Noise information corresponding to the P second nodes respectively by the first node
Figure FDA00032980894000000124
Summing or matrix splicing is carried out to obtain the equivalent noise information->
Figure FDA00032980894000000125
10. The method according to claim 6 or 7, wherein the first node corresponds noise-related information to the P second nodes respectively
Figure FDA00032980894000000126
Performing parameter fusion to obtain equivalent noise related information->
Figure FDA00032980894000000127
The method comprises the following steps:
noise related information corresponding to the P second nodes by the first node
Figure FDA00032980894000000128
Summing or matrix splicing is carried out to obtain the relevant information of the equivalent noise>
Figure FDA0003298089400000021
11. Method according to any of claims 6 to 10, characterized in that said equalization information W H The following formula is satisfied:
Figure FDA0003298089400000022
12. the method according to any one of claims 1 to 11, further comprising:
and the first node performs signal fusion on the first signals respectively received by the P second nodes to obtain the second signals.
13. The method according to claim 12, wherein the signal fusion of the first signals received by the P second nodes by the first node to obtain the second signals comprises:
and the first node sums or performs matrix splicing on the first signals respectively received by the P second nodes to obtain the second signals.
14. The method of any of claims 1 to 13, wherein the first signal is a compressed matrix
Figure FDA0003298089400000023
Weighted compression matrix, the compression matrix>
Figure FDA0003298089400000024
Is determined based on the channel parameters.
15. The method according to any one of claims 1 to 14, wherein the P second nodes comprise a first node and P-1 third nodes or the P second nodes comprise P third nodes, and the third nodes are child nodes of the first node.
16. A method of processing a signal, comprising:
the second node sends channel parameters to the first node, wherein the channel parameters comprise channel information
Figure FDA0003298089400000025
And a first parameter comprising noise-related information ≥>
Figure FDA0003298089400000026
Or noise information->
Figure FDA0003298089400000027
The noise-related information->
Figure FDA0003298089400000028
M for indicating the second node corresponds to c Of an antennaInter-noise correlation, said noise information &>
Figure FDA0003298089400000029
For indicating noise of a first signal received by said second node, P being an integer greater than 1, M c Is an integer greater than 0.
17. The method of claim 16, wherein the channel parameter is a compressed matrix
Figure FDA00032980894000000210
Weighted, the compression matrix->
Figure FDA00032980894000000211
Is determined based on the channel parameters.
18. The method of claim 17, wherein the compression matrix is a compressed matrix
Figure FDA00032980894000000212
Is L M c Dimension matrix, where L is H c The number of columns.
19. The method of claim 17 or 18, wherein the compression matrix is a compressed matrix
Figure FDA00032980894000000213
The following formula is satisfied:
Figure FDA00032980894000000214
wherein H c For channel information before compression, R cc Is the noise related information before compression.
20. The method of any one of claims 16 to 19Wherein the first signal is a compressed matrix
Figure FDA00032980894000000215
Weighted compression matrix, the compression matrix>
Figure FDA00032980894000000216
Is determined based on the channel parameters.
21. A communications apparatus, comprising:
a transceiving unit, configured to obtain channel parameters corresponding to the P second nodes, where the channel parameters include channel information
Figure FDA00032980894000000217
And a first parameter comprising noise-related information ≥>
Figure FDA00032980894000000218
Or noise information>
Figure FDA00032980894000000219
Said noise related information &>
Figure FDA00032980894000000220
M for indicating the second node corresponds to c Noise correlation between individual antennas, the noise information &>
Figure FDA00032980894000000223
For indicating noise of a first signal received by said second node, P being an integer greater than 1, M c Is an integer greater than 0;
and the processing unit is configured to determine equalization information according to the channel parameters corresponding to the P second nodes, where the equalization information is used to perform channel equalization on a second signal, and the second signal is determined according to the first signals received by the P second nodes, respectively.
22. The apparatus of claim 21, wherein the channel parameter is a compressed matrix
Figure FDA00032980894000000221
Weighted compression matrix, the compression matrix>
Figure FDA00032980894000000222
Is determined based on the channel parameters.
23. The apparatus of claim 22, wherein the compression matrix is based on a number of bits of the signal
Figure FDA0003298089400000031
Is L x M c Dimension matrix, wherein L is H c The number of columns.
24. The apparatus of claim 22 or 23, wherein the compression matrix is a matrix of bits
Figure FDA0003298089400000032
The following formula is satisfied:
Figure FDA0003298089400000033
wherein H c For channel information before compression, R cc Is the noise related information before compression.
25. The apparatus according to any one of claims 21 to 24, wherein the processing unit is specifically configured to:
performing parameter fusion on the channel parameters respectively corresponding to the P second nodes to obtain equivalent parameters;
and determining the balance information according to the equivalent parameters.
26. The apparatus according to claim 25, wherein the processing unit is specifically configured to:
channel information corresponding to the P second nodes respectively
Figure FDA0003298089400000034
Performing parameter fusion to obtain equivalent channel information->
Figure FDA0003298089400000035
And the combination of (a) and (b),
respectively corresponding noise information to the P second nodes
Figure FDA0003298089400000036
Performing parameter fusion to obtain equivalent noise information->
Figure FDA0003298089400000037
Or the noise related information corresponding to the P second nodes is/are combined>
Figure FDA0003298089400000038
Performing parameter fusion to obtain equivalent noise related information->
Figure FDA0003298089400000039
27. The apparatus of claim 26, wherein the processing unit is further configured to:
according to the equivalent noise information
Figure FDA00032980894000000310
Determining equivalent noise related information &>
Figure FDA00032980894000000311
28. The apparatus according to claim 26 or 27, wherein the processing unit is specifically configured to:
channel information corresponding to the P second nodes respectively
Figure FDA00032980894000000312
Summing or matrix splicing is carried out to obtain the equivalent channel information->
Figure FDA00032980894000000313
29. The apparatus according to claim 26 or 27, wherein the processing unit is specifically configured to:
noise information respectively corresponding to the P second nodes
Figure FDA00032980894000000314
Summing or matrix splicing is carried out to obtain the equivalent noise information->
Figure FDA00032980894000000315
30. The apparatus according to claim 26 or 27, wherein the processing unit is specifically configured to:
noise-related information corresponding to the P second nodes respectively
Figure FDA00032980894000000316
Summing or matrix splicing is carried out to obtain the relevant information of the equivalent noise>
Figure FDA00032980894000000317
/>
31. The apparatus according to any of the claims 26 to 30, wherein said equalization information W H Satisfy the following disclosureFormula (II):
Figure FDA00032980894000000318
32. the apparatus according to any one of claims 21 to 31, wherein the processing unit is further configured to:
and performing signal fusion on the first signals respectively received by the P second nodes to obtain the second signals.
33. The apparatus according to claim 32, wherein the processing unit is specifically configured to:
and summing or matrix splicing the first signals respectively received by the P second nodes to obtain the second signals.
34. The apparatus of any of claims 21 to 33, wherein the first signal is a compressed matrix
Figure FDA00032980894000000319
Weighted, the compression matrix->
Figure FDA00032980894000000320
Is determined based on the channel parameters.
35. The apparatus according to any of claims 21 to 34, wherein the P second nodes comprise the communication apparatus and P-1 third nodes or the P second nodes comprise P third nodes, the third nodes being child nodes of the communication apparatus.
36. A communications apparatus, comprising:
a transceiving unit for transmitting a channel parameter to a first node, the channel parameter including channel information
Figure FDA00032980894000000321
And a first parameter comprising noise-related information ≥>
Figure FDA00032980894000000322
Or noise information->
Figure FDA00032980894000000323
Said noise related information &>
Figure FDA00032980894000000324
M for indicating correspondence of the communication device c Noise correlation between individual antennas, the noise information &>
Figure FDA00032980894000000325
For indicating the noise of a first signal received by said communication device, P being an integer greater than 1, M c Is an integer greater than 0.
37. The apparatus of claim 36, wherein the channel parameter is a compressed matrix
Figure FDA0003298089400000041
Weighted compression matrix, the compression matrix>
Figure FDA0003298089400000042
Is determined based on the channel parameters.
38. The apparatus of claim 37, wherein the compression matrix
Figure FDA0003298089400000043
Is L M c Dimension matrix, where L is H c The number of columns.
39. The apparatus of claim 37 or 38, wherein the compression matrix is a matrix of bits
Figure FDA0003298089400000044
The following formula is satisfied:
Figure FDA0003298089400000045
wherein H c For channel information before compression, R cc Is noise related information before compression.
40. The apparatus of any of claims 36 to 39, wherein the first signal is a compressed matrix
Figure FDA0003298089400000046
Weighted, the compression matrix->
Figure FDA0003298089400000047
Is determined based on the channel parameters.
41. A communications device comprising logic circuitry and an input output interface, wherein the input output interface is arranged to receive signals from a communications device other than the device and transmit them to the logic circuitry or to transmit signals from the logic circuitry to a communications device other than the device, and wherein the logic circuitry is arranged to execute code instructions to implement the method of any one of claims 1 to 20.
42. A chip, comprising: a processor for retrieving and executing computer instructions from the memory to cause the device on which the chip is installed to perform the method of any one of claims 1 to 20.
43. A computer-readable storage medium for storing computer program instructions, the computer program causing a computer to perform the method of any one of claims 1 to 20.
44. A computer program product comprising computer program instructions to cause a computer to perform the method of any one of claims 1 to 20.
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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117938591A (en) * 2024-01-31 2024-04-26 中南大学 Low-complexity single-carrier time domain equalization method and device

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117938591A (en) * 2024-01-31 2024-04-26 中南大学 Low-complexity single-carrier time domain equalization method and device

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