CN115087011B

CN115087011B - Method and device for detecting downlink signal of flexible frame structure simulation system

Info

Publication number: CN115087011B
Application number: CN202210700348.6A
Authority: CN
Inventors: 曹艳霞; 王金石; 张忠皓
Original assignee: China United Network Communications Group Co Ltd
Current assignee: China United Network Communications Group Co Ltd
Priority date: 2022-06-20
Filing date: 2022-06-20
Publication date: 2024-04-12
Anticipated expiration: 2042-06-20
Also published as: CN115087011A

Abstract

The application discloses a downlink signal detection method and device of a flexible frame structure simulation system, relates to the technical field of communication, and is used for comprehensively and accurately determining the signal quality of a downlink signal of a terminal. The flexible frame structure simulation system comprises a serving cell and an interference cell of the terminal. The method comprises the following steps: determining the signal strength of a first downlink signal of a terminal, a first interference value of a plurality of interference downlink signals on the first downlink signal and a second interference value of noise on the first downlink signal; according to a preset neural network algorithm, determining an interference elimination factor of an interference terminal, and calculating a third interference value of an interference uplink signal to a first downlink signal according to the interference elimination factor, signal transmitting power of the interference terminal and link loss between the interference terminal and the terminal; and accurately and comprehensively determining the signal-to-noise ratio of the first downlink signal according to the signal strength of the first downlink signal and the interference values of a plurality of interference sources such as the first interference value, the second interference value and the third interference value.

Description

Method and device for detecting downlink signal of flexible frame structure simulation system

Technical Field

The embodiment of the application relates to the technical field of communication, in particular to a downlink signal detection method and device of a flexible frame structure simulation system.

Background

In a communication system having a time division duplex (time division duplexing, TDD) mode, a cell may use different time slots of the same frequency channel (i.e., carrier) to enable transmission and reception of signals. That is, the cell may allocate uplink and downlink of the communication system to the same spectrum through the TDD technology. The uplink and the downlink occupy different time periods respectively, so that wireless resources can be fully used, and the asymmetric characteristics of different services are adapted.

In a communication system with TDD mode, different subframe configuration structures are defined, which may include DSUUU, DDSUU and DDDSU, for example. Where D denotes a Downlink slot (Downlink slot) refers to a slot for Downlink transmission. S denotes a Special slot (Special slot) refers to a slot for downlink transmission or uplink transmission. U denotes an Uplink slot (Uplink slot) and refers to a slot for Uplink transmission. In this way, the cell can flexibly select proper subframe structure configuration according to the uplink and downlink traffic carried by the cell, so that the uplink and downlink bandwidth transmission traffic configured by the subframe structure is used. However, when different cells adopt different subframe configuration structures to send downlink signals to the terminal, the downlink signals received by the terminal can be interfered by cross time slots. At this time, the downlink signal received by the terminal needs to be detected to determine the signal quality of the downlink signal.

Disclosure of Invention

The application provides a downlink signal detection method and device of a flexible frame structure simulation system, which are used for comprehensively and accurately detecting downlink signals received by a terminal so as to determine the signal quality of the downlink signals.

In order to achieve the above purpose, the present application adopts the following technical scheme:

in a first aspect, a downlink signal detection method of a flexible frame structure simulation system is provided, where the flexible frame structure simulation system includes a serving cell and a plurality of interfering cells of a target terminal, and the method includes: determining the signal strength of a first downlink signal received by a target terminal, and determining first interference values of downlink signals of a plurality of interference cells on the first downlink signal and second interference values of noise on the first downlink signal; according to a preset neural network algorithm, determining an interference elimination factor of an interference terminal, and calculating a third interference value of an uplink signal of the interference terminal to a first downlink signal according to the interference elimination factor of the interference terminal, the signal transmitting power of the interference terminal and the link loss between the interference terminal and a target terminal, wherein the uplink signal of the interference terminal interferes with the first downlink signal, and the interference elimination factor of the interference terminal is used for representing the interference degree of the uplink signal sent by the interference terminal to the first signal; and determining the signal-to-noise ratio of the first downlink signal according to the signal strength of the first downlink signal, the first interference value, the second interference value and the third interference value.

Based on the technical scheme provided by the application, when the service cell adopts the flexible frame structure to send the downlink signal to the terminal, the downlink signal from the service cell received by the terminal can be interfered by the downlink signal and the uplink signal of the adjacent cell. Therefore, in the embodiment of the present application, the signal to noise ratio of the downlink signal from the serving cell received by the terminal may be calculated according to the interference values (may also be referred to as interference power) of a plurality of interference sources (for example, the downlink signal of the interfering cell, noise, uplink signal of the interfering terminal, etc.) that generate interference to the downlink signal from the serving cell received by the terminal. Because the signal-to-noise ratio of the signal can reflect the signal quality of the signal, the technical scheme provided by the embodiment of the application can comprehensively and accurately evaluate the signal quality of the downlink signal received by the terminal.

In a possible implementation manner, the plurality of interference cells include a strong interference cell and a weak interference cell, the strong interference cell is an interference cell, in the plurality of interference cells, with a large-scale path loss between the strong interference cell and a target terminal being greater than or equal to a preset threshold, and the weak interference cell is an interference cell, in the plurality of interference cells, with a large-scale path loss between the weak interference cell and the target terminal being less than the preset threshold, where the determining "determining a first interference value of downlink signals of the plurality of interference cells to downlink signals of the target terminal" includes: calculating the interference value of the downlink signal of the strong interference cell on the first downlink signal according to the signal transmitting power of the strong interference cell, the channel matrix between the target terminal and the strong interference cell and the precoding matrix of the strong interference cell; according to the signal transmitting power of the weak interference cell and the link loss from the target terminal to the weak interference cell, calculating the interference value of the downlink signal of the weak interference cell on the first downlink signal, wherein the first interference value comprises: the interference value of the downlink signal of the strong interference cell to the downlink signal of the service cell and the interference value of the downlink signal of the weak interference cell to the downlink signal of the service cell.

In a possible implementation manner, the method for determining the interference cancellation factor of the interfering terminal according to the preset neural network algorithm specifically includes: acquiring configuration information of a target terminal, configuration information of a serving cell, configuration information of an interference cell and configuration information of an interference terminal, wherein the configuration information comprises antenna configuration information and/or position information; and inputting the configuration information of the target terminal, the configuration information of the serving cell, the configuration information of the interference cell and the configuration information of the interference terminal into a preset neural network model to obtain an interference elimination factor.

In a possible implementation manner, the method further includes: calculating the antenna gain of the target terminal and the antenna gain of the interference terminal through simulation, and determining the large-scale path loss between the target terminal and the interference terminal; and determining the link loss between the target terminal and the interference terminal according to the difference value between the large-scale path loss and the antenna gain of the target terminal and the antenna gain of the interference terminal.

In a possible implementation manner, the method further includes: establishing a channel matrix between a target terminal and a serving cell through simulation; determining a signal when a downlink signal sent by a serving cell reaches a target terminal according to the signal transmitting power of the serving cell, a channel matrix between the target terminal and the serving cell and a precoding matrix of the serving cell; and based on a preset detection algorithm, linearly detecting a signal when the downlink signal sent by the serving cell reaches the target terminal to obtain a first downlink signal.

In a possible implementation manner, the signal strength of the first downlink signal satisfies a first formula, where the first formula is: s1=p|dhw| ² The method comprises the steps of carrying out a first treatment on the surface of the Wherein S1 is the signal strength of the first downlink signal, P is the signal transmitting power of the serving cell, D is a preset detection matrix, H is a channel matrix between the serving cell and the target terminal, and W is a precoding matrix of the serving cell.

In a possible implementation manner, the signal-to-noise ratio of the first downlink signal satisfies a second formula, where the second formula is: sinr=s1/(s1+b1+b2+b3); wherein, SINR is the signal-to-noise ratio of the first downlink signal, S1 is the signal strength of the first downlink signal, B1 is the first interference value, B2 is the second interference value, and B3 is the third interference value.

In a second aspect, a downlink signal detection apparatus of a flexible frame structure simulation system is provided, where the flexible frame structure simulation system includes a serving cell and a plurality of interfering cells of a target terminal, and the downlink signal detection apparatus may be a functional module for implementing the method in the first aspect or any possible design of the first aspect. The downlink signal detecting device may implement the functions performed in the above aspects or in each possible design, where the functions may be implemented by hardware executing corresponding software. The hardware or software comprises one or more modules corresponding to the functions. Such as: the downlink signal detection device comprises a determination unit and a processing unit.

And the determining unit is used for determining the signal strength of the first downlink signal received by the target terminal and determining the first interference value of the downlink signals of the plurality of interference cells on the first downlink signal and the second interference value of noise on the first downlink signal.

The processing unit is used for determining an interference elimination factor of the interference terminal according to a preset neural network algorithm, calculating a third interference value of an uplink signal of the interference terminal to the first downlink signal according to the interference elimination factor of the interference, the signal transmitting power of the interference terminal and the link loss between the interference terminal and the target terminal, wherein the uplink signal of the interference terminal interferes with the first downlink signal, and the interference elimination factor of the interference terminal is used for representing the interference degree of the uplink signal sent by the interference terminal to the first signal.

The processing unit is further configured to determine a signal-to-noise ratio of the first downlink signal according to the signal strength of the first downlink signal, the first interference value, the second interference value, and the third interference value.

The specific implementation manner of the downlink signal detection device may refer to the behavior function of the downlink signal detection method of the flexible frame structure simulation system provided by the first aspect or any possible design of the first aspect, and will not be repeated here. Therefore, the downlink signal detection device of the flexible frame structure simulation system can achieve the same beneficial effects as the first aspect or any possible design of the first aspect.

In a possible implementation manner, the plurality of interference cells include a strong interference cell and a weak interference cell, the strong interference cell is an interference cell, in which a large-scale path loss between the plurality of interference cells and the target terminal is greater than or equal to a preset threshold, and the weak interference cell is an interference cell, in which a large-scale path loss between the plurality of interference cells and the target terminal is less than the preset threshold, and the determining unit is specifically configured to: calculating the interference value of the downlink signal of the strong interference cell on the first downlink signal according to the signal transmitting power of the strong interference cell, the channel matrix between the target terminal and the strong interference cell and the precoding matrix of the strong interference cell; according to the signal transmitting power of the weak interference cell and the link loss from the target terminal to the weak interference cell, calculating the interference value of the downlink signal of the weak interference cell on the first downlink signal, wherein the first interference value comprises: the interference value of the downlink signal of the strong interference cell to the downlink signal of the service cell and the interference value of the downlink signal of the weak interference cell to the downlink signal of the service cell.

In a possible implementation manner, the processing unit is specifically configured to: acquiring configuration information of a target terminal, configuration information of a serving cell, configuration information of an interference cell and configuration information of an interference terminal, wherein the configuration information comprises antenna configuration information and/or position information; and inputting the configuration information of the target terminal, the configuration information of the serving cell, the configuration information of the interference cell and the configuration information of the interference terminal into a preset neural network model to obtain an interference elimination factor.

In a possible implementation manner, the determining unit is further configured to calculate, through simulation, an antenna gain of the target terminal and an antenna gain of the interference terminal, and determine a large-scale path loss between the target terminal and the interference terminal; and the processing unit is also used for determining the link loss between the target terminal and the interference terminal according to the difference value between the large-scale path loss and the antenna gain of the target terminal and the antenna gain of the interference terminal.

In a possible implementation manner, the downlink signal detection device further includes a building unit, configured to build a channel matrix between the target terminal and the serving cell through simulation; the processing unit is used for determining the signal when the downlink signal sent by the serving cell reaches the target terminal according to the signal transmitting power of the serving cell, the channel matrix between the target terminal and the serving cell and the precoding matrix of the target terminal, and carrying out linear detection on the signal when the downlink signal sent by the serving cell reaches the target terminal based on a preset detection algorithm to obtain a first downlink signal.

In a possible implementation manner, the signal strength of the first downlink signal satisfies a first formula, where the first formula is: s1=p|dhw| ² The method comprises the steps of carrying out a first treatment on the surface of the Wherein S1 is the signal strength of the downlink signal, P is the signal transmitting power of the serving cell, D is a preset detection matrix, H is a channel matrix between the serving cell and the target terminal, and W is a precoding matrix of the target terminal.

In a third aspect, a downstream signal detection apparatus (hereinafter, for convenience of description, simply referred to as downstream signal detection apparatus) of a flexible frame structure simulation system is provided. The downstream signal detection device may implement the functions performed in the above aspects or in each possible design, where the functions may be implemented by hardware, for example: in one possible design, the downlink signal detecting apparatus may include: a processor and a communication interface, the processor being operable to support the downstream signal detection means to carry out the functions involved in the first aspect or any one of the possible designs of the first aspect, for example: and the processor determines an interference elimination factor of the interference terminal according to a preset neural network algorithm.

In yet another possible design, the downstream signal detection device may further include a memory for storing computer-executable instructions and data necessary for the downstream signal detection device. When the downlink signal detecting device is operated, the processor executes the computer-executed instructions stored in the memory, so that the downlink signal detecting device executes any one of the possible downlink signal detecting methods of the first aspect or the first aspect for designing the flexible frame structure simulation system.

In a fourth aspect, a computer readable storage medium is provided, which may be a readable non-volatile storage medium, where computer instructions or a program are stored, which when run on a computer, cause the computer to perform the above first aspect or any one of the above aspects of the possible downstream signal detection methods of designing the flexible frame structure simulation system.

In a fifth aspect, a computer program product is provided comprising instructions which, when run on a computer, enable the computer to perform the method of downstream signal detection of the flexible frame structure simulation system of the first aspect or any one of the possible designs of the aspects.

In a sixth aspect, a chip system is provided, where the chip system includes a processor and a communication interface, where the chip system may be configured to implement a function performed by the downlink signal detection device of the flexible frame structure simulation system in the first aspect or any of the possible designs of the first aspect, where the processor is configured to determine, for example, a signal strength of a first downlink signal received by a target terminal. In one possible design, the chip system further includes a memory for holding program instructions and/or data. The chip system may be composed of a chip, or may include a chip and other discrete devices, without limitation.

The technical effects of any one of the design manners of the second aspect to the sixth aspect may be referred to the technical effects of the first aspect, and will not be described herein.

Drawings

Fig. 1 is a schematic structural diagram of another communication system according to an embodiment of the present application;

fig. 2 is a schematic structural diagram of another communication system according to an embodiment of the present application;

fig. 3 is a schematic structural diagram of a downlink signal detection apparatus 300 according to an embodiment of the present application;

fig. 4 is a flow chart of a downlink signal detection method provided in an embodiment of the present application;

Fig. 5 is a flowchart of a training method of a preset neural network model according to an embodiment of the present application;

fig. 6 is a schematic structural diagram of a neural network according to an embodiment of the present application;

fig. 7 is a schematic diagram of a downlink signal detection method of another flexible frame structure simulation system according to an embodiment of the present application;

fig. 8 is a schematic diagram of a downlink signal detection method of another flexible frame structure simulation system according to an embodiment of the present application;

fig. 9 is a schematic structural diagram of another downlink signal detecting apparatus 90 according to an embodiment of the present application.

Detailed Description

In order to enable those skilled in the art to better understand the technical solutions of the present disclosure, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings.

It should be noted that the terms "first," "second," and the like in the description and claims of the present application and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the disclosure described herein may be capable of operation in sequences other than those illustrated or described herein. The implementations described in the following exemplary examples are not representative of all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with aspects of embodiments of the present application as detailed in the accompanying claims.

It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, and/or components.

In order to ensure that the constructed cells can bring the maximum throughput gain, the communication quality of the planned communication system can be evaluated and analyzed in a simulation mode before the actual networking. For example, for a New Radio (NR) cell in a communication system having a TDD model, the NR cell uses a millimeter wave band for transmission data of signals. However, the millimeter wave band has poor penetrability, and in an environment with good isolation, the NR cell can adopt a flexible frame mode, and the data can be transmitted by using bandwidths corresponding to different subframe configuration structures. However, when the NR cell uses a flexible frame to perform signal transmission with the terminal, a problem of cross slot interference is introduced, which easily causes a decrease in system capacity.

In general, the signal quality of the downlink signal received by the terminal may be determined by a signal-to-noise ratio. For example, the block error rate of the downlink signal may be mapped by the signal-to-noise ratio, so that the data throughput of the terminal may be calculated. Therefore, in order to evaluate the network quality of the communication system, simulations may be performed to determine the signal-to-noise ratio of the downlink signal received by the terminal before networking.

In the simulation scene, when the cell and the terminal adopt the same frame structure to carry out signal transmission, the downlink signal sent by the cell to the terminal can be interfered by the downlink signal sent by the interference cell in the same time slot. When a detected cell (hereinafter, for distinguishing from an interfering cell, the detected cell is referred to as a serving cell) receives a downlink signal from the serving cell, the downlink signal received by the target terminal may be calculated by the following formula one.

Wherein y represents a signal when a downlink signal transmitted by a serving cell reaches a target terminal. P (P) ₁ The signal transmission power used when the serving cell transmits a downlink signal to the target terminal is indicated. H _1s Representing target terminal and serving cellA channel matrix between. The channel matrix has an order of np×nb. The elements in the channel matrix represent the frequency domain channel response between the antennas of the target terminal and the antennas of the serving cell. Np is the number of antennas of the target terminal, and Nb is the number of antennas of the serving cell. W (W) ₁ Representing the precoding matrix of the serving cell. The precoding matrix has an order of nb×m1. M1 is the number of signal streams of the downstream signal. X is x ₁ ＝(x _1.1 ，x _1.2 ，…，x _1.M ) ^T Normalized vector of useful signal sent for target terminal. P (P) _i Indicating the signal transmit power used when the strong interfering cell transmits the downlink signal. H _1g Representing the channel matrix between the target terminal and the strongly interfering cell. W (W) _i Representing the precoding matrix of the strong interfering cell. X is x _i ＝(x ₁ ，x ₂ ，…，x _Mj ) ^T A normalized vector representing the signal transmitted by the interfering terminal. z is noise, z= (z) ₁ ，z ₂ ，…，z _Nr ) ^T . The elements in z are CN (0, sigma ² )。σ ² Is the variance of the noise. P (P) _w Representing the signal transmit power of the weak interfering cell. L (L) _ig Indicating the link loss between the target terminal and the weak interfering cell. The link loss may include a large scale path loss and antenna gain. The calculation method of the large-scale path loss and the antenna gain can refer to the prior art, and will not be repeated.

The interfering terminal may refer to a terminal that generates interference to a downlink signal received by the target terminal. The interfering cell may refer to a cell in which a transmitted downlink signal can interfere with a downlink signal of a serving cell. The interfering cells may include strong interfering cells and weak interfering cells.

For example, as shown in fig. 1, a communication system is provided in an embodiment of the present application. The communication system may include a plurality of cells (e.g., cell 1 and cell 2) and a plurality of terminals (e.g., terminal 1 and terminal 2). Each of the plurality of cells may serve a terminal accessing the cell. For example, cell 1 may provide communication services for terminal 1 and cell 2 may provide communication services for terminal 2.

For terminal 1, cell 1 may be referred to as a serving cell. When the cell 1 and the cell 2 use the same frame structure and the same time slot to transmit the downlink signal, the downlink signal transmitted by the cell 2 to the terminal 2 may generate interference to the downlink signal transmitted by the cell 1 to the terminal 1. At this time, the cell 2 may be referred to as a cell 1 and an interfering cell of the terminal 1.

If the large-scale path loss from the cell 2 to the terminal 1 is greater than or equal to a preset threshold, the cell 2 may be referred to as a strong interference cell of the terminal 1; if the large-scale path loss of cell 2 to terminal 1 is less than a preset threshold, cell 2 may be referred to as a weak interfering cell of terminal 1.

Alternatively, if the terminal 1 has a plurality of interfering cells, the plurality of interfering cells may be ranked according to the magnitude of the large-scale path loss from the interfering cells to the terminal 1, and the first N interfering cells may be used as strong interfering cells of the terminal 1, and the remaining interfering cells may be used as weak interfering cells of the terminal 1. N is a positive integer less than the number of interfering cells.

At the signal receiving end, the combined effect of inter-symbol interference (ISI) and noise on the signal is reduced in order to reduce the distortion of the signal. The signal receiving end (e.g., the target terminal) may perform linear detection on the signal to obtain a detected signal (i.e., a recovered original signal).

For example, the target terminal may detect the received downlink signal by using a preset linear detection algorithm. The preset linear detection algorithm may be Zero Forcing (ZF), minimum mean square error (minimum mean square error, MMSE), or the like, but may be other linear detection algorithms, which are not limited.

In an example, the target terminal may perform linear detection on the received downlink signal by using a preset detection matrix, so as to obtain a detected downlink signal.

For example, the detection matrix is preset to be D, and the order of D is m1×np. The detected downstream signal is:

wherein,and representing the downlink signal received by the target terminal, wherein the downlink signal comprises a useful signal and an inter-stream interference signal. />Representing the interference signals of other terminals in a multi-user (MU) paired terminal group and the interference signals of strong interfering cells. The MU paired terminal group includes one or more interfering terminals of the target terminal. Dz represents noise disturbance. />Representing the interfering signal of a weak interfering cell.

For convenience of description, the detected downlink signal may be modified as follows:

wherein,

for any signal stream (such as an mth signal stream) in the downlink signal received by the target terminal, the signal after linear detection of the mth signal stream is:

Wherein A is _m Is the m-th line element of a. B (B) _im Is B _i Is the m-th line element of (c).

The signal-to-noise ratio of the mth signal is:

wherein A is _mj Is the mth row and the jth column element of A. B (B) _imj Is B _i The mth row and the jth column elements of (c). D (D) _mj Is the mth row and the jth column element of D.

In another simulation scenario, when the cell and the terminal adopt a flexible frame structure to perform signal transmission, the downlink signal sent by the cell is not only interfered by the downlink signal of the interference cell in the same time slot, but also can be interfered by the uplink signal of the interference terminal.

For example, as shown in fig. 2, when an interfering terminal transmits an uplink signal to an interfering cell, the uplink signal may be received by a serving cell. When the interference cell is the same as the time slot resource used by the target terminal, the uplink signal will interfere with the downlink signal received by the target terminal. Meanwhile, the uplink signal sent by the interference cell to the interference terminal can also generate interference to the downlink signal sent by the service cell.

In view of this, the embodiment of the present application provides a downlink signal detection method of a flexible frame structure simulation system, when a serving cell adopts a flexible frame structure to send a downlink signal to a terminal, the downlink signal received by the terminal from the serving cell may be interfered by the downlink signal and the uplink signal of an adjacent cell. Based on this, in the embodiment of the present application, the signal to noise ratio of the downlink signal from the serving cell received by the terminal may be calculated according to the interference values (may also be referred to as interference power) of a plurality of interference sources (for example, the downlink signal of the interfering cell, noise, uplink signal of the interfering terminal, etc.) that generate interference to the downlink signal from the serving cell received by the terminal. Because the signal-to-noise ratio of the signal can reflect the signal quality of the signal, the technical scheme provided by the embodiment of the application can comprehensively and accurately evaluate the signal quality of the downlink signal received by the terminal.

It should be noted that, the communication systems shown in fig. 1 and fig. 2 are communication systems constructed by simulation by the simulation device. The cells and terminals in fig. 1 and 2 are both in the same simulation system. The method in the embodiment of the application simulates the actual communication environment through simulation, so that the signal-to-noise ratio of the downlink signal of the cell is obtained. Thus, when networking is performed later, communication engineering personnel can adjust or optimize the cell to be planned according to the simulation result.

The method provided in the embodiments of the present application will be described in detail below with reference to the accompanying drawings.

It should be noted that, the network system described in the embodiments of the present application is for more clearly describing the technical solution of the embodiments of the present application, and does not constitute a limitation on the technical solution provided in the embodiments of the present application, and those skilled in the art can know that, with the evolution of the network system and the appearance of other network systems, the technical solution provided in the embodiments of the present application is applicable to similar technical problems.

In an example, the embodiment of the present application further provides a downlink signal detection device (hereinafter, for convenience of description, simply referred to as a signal detection device) of the flexible frame structure simulation system, where the signal detection device may be used to perform the method of the embodiment of the present application. For example, the downlink signal detection device may be a simulation device, or may be a device in the simulation device. The downstream signal detection means may be provided with simulation software which may be used to perform the simulation process.

For example, as shown in fig. 3, a schematic diagram of a signal detection apparatus 300 according to an embodiment of the present application is provided. The downstream signal detection device 300 may include a processor 301, a communication interface 302, and a communication line 303.

Further, the signal detection device 300 may further include a memory 304. The processor 301, the memory 304, and the communication interface 302 may be connected by a communication line 303.

The processor 301 is a CPU, general-purpose processor, network processor (network processor, NP), digital signal processor (digital signal processing, DSP), microprocessor, microcontroller, programmable logic device (programmable logic device, PLD), or any combination thereof. The processor 301 may also be any other device having processing functions, such as, without limitation, a circuit, a device, or a software module.

A communication interface 302 for communicating with other devices or other communication networks. The communication interface 302 may be a module, a circuit, a communication interface, or any device capable of enabling communication.

A communication line 303 for transmitting information between the components included in the downstream signal detection device 300 of the flexible frame structure simulation system.

Memory 304 for storing instructions. Wherein the instructions may be computer programs.

The memory 304 may be, but not limited to, a read-only memory (ROM) or other type of static storage device capable of storing static information and/or instructions, a random access memory (random access memory, RAM) or other type of dynamic storage device capable of storing information and/or instructions, an EEPROM, a CD-ROM (compact disc read-only memory) or other optical disk storage, an optical disk storage (including compact disk, laser disk, optical disk, digital versatile disk, blu-ray disk, etc.), a magnetic disk storage medium or other magnetic storage device, etc.

It should be noted that the memory 304 may exist separately from the processor 301 or may be integrated with the processor 301. Memory 304 may be used to store instructions or program code or some data, etc. The memory 304 may be located in the downlink signal detection apparatus 300 of the flexible frame structure simulation system, or may be located outside the downlink signal detection apparatus 300 of the flexible frame structure simulation system, without limitation. The processor 301 is configured to execute the instructions stored in the memory 304, so as to implement a downlink signal detection method of the flexible frame structure simulation system provided in the following embodiments of the present application.

In one example, processor 301 may include one or more CPUs, such as CPU0 and CPU1 in fig. 3.

As an alternative implementation, the downlink signal detection apparatus 300 of the flexible frame structure simulation system includes a plurality of processors, for example, may include the processor 307 in addition to the processor 301 in fig. 3.

As an alternative implementation, the downlink signal detecting apparatus 300 of the flexible frame structure simulation system further includes an output device 305 and an input device 306. Illustratively, the input device 306 is a keyboard, mouse, microphone, or joystick device, and the output device 305 is a display screen, speaker (spaker), or the like.

It should be noted that the downlink signal detecting apparatus 300 may be a desktop computer, a portable computer, a network server, a mobile phone, a tablet computer, a wireless terminal, an embedded device, a chip system, or a device having a similar structure in fig. 3. Further, the constituent structure shown in fig. 3 is not limited, and may include more or less components than those shown in fig. 3, or may combine some components, or may be arranged differently, in addition to those shown in fig. 3.

In the embodiment of the application, the chip system may be formed by a chip, and may also include a chip and other discrete devices.

Further, actions, terms, etc. referred to between embodiments of the present application may be referred to each other without limitation. In the embodiment of the present application, the name of the message or the name of the parameter in the message, etc. interacted between the devices are only an example, and other names may also be adopted in the specific implementation, and are not limited.

It should be noted that, in the embodiments of the present application, words such as "exemplary" or "such as" are used to mean serving as an example, instance, or illustration. Any embodiment or design described herein as "exemplary" or "for example" should not be construed as preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary" or "such as" is intended to present related concepts in a concrete fashion.

In the present application, "at least one" means one or more, and "a plurality" means two or more. "and/or", describes an association relationship of an association object, and indicates that there may be three relationships, for example, a and/or B, and may indicate: a alone, a and B together, and B alone, wherein a, B may be singular or plural. The character "/" generally indicates that the context-dependent object is an "or" relationship. "at least one of" or the like means any combination of these items, including any combination of single item(s) or plural items(s). For example, at least one (one) of a, b, or c may represent: a, b, c, a-b, a-c, b-c, or a-b-c, wherein a, b, c may be single or plural.

The following describes a downlink signal detection method of the flexible frame structure simulation system provided in the embodiment of the present application with reference to the network architecture shown in fig. 2.

It should be noted that, as shown in fig. 4, the method provided in the embodiment of the present application includes a pre-simulation stage and a simulation stage.

In the pre-simulation stage, training sample data can be trained according to a preset neural network algorithm, so that a preset neural network model is obtained. During the simulation phase, simulation tasks may be performed. For example, the simulation device may determine the interference cancellation factor according to a preset neural network model obtained in the pre-simulation stage, and simulate to obtain the signal-to-noise ratio of the downlink signal of the serving cell according to the interference values of multiple interference sources. The pre-simulation stage and the simulation stage are described below.

1. In the pre-simulation stage, the device comprises a pre-simulation stage,

as shown in fig. 5, the model training method provided in the embodiment of the present application may be S501 and S502.

S501, acquiring a plurality of training sample data.

The data source for acquiring the training sample data may include one or more of a data source 1, a data source 2 and a data source 3. The data source 1 may refer to data of a strong interference user of a downlink same time slot of a target terminal when a cell adopts a same frame structure. The data source 2 may refer to data of a strong interference user of an uplink cross slot of the target terminal when the cell adopts a flexible frame structure. The data source 3 may refer to data of a strong interference user of an uplink cross slot and a strong interference user of a downlink same slot of the target terminal when the cell adopts a flexible frame structure.

Wherein each training sample data may include configuration information of the detected user and configuration information of the interfering user. For example, the configuration information of the detected user may include antenna configuration parameters (such as the number of array elements, the number of channels, and antenna position information) of the detected terminal, and antenna position information of a serving cell of the detected terminal. The configuration information of the interfering user may include antenna position information of the interfering cell and position information and signal transmission power of the interfering terminal, and an interference cancellation factor of the interfering terminal. The interference cancellation factor of the interfering terminal may reflect the interference degree of the signal of the interfering terminal to the downlink signal received by the detected terminal. The interference cancellation factor is greater than 0 and less than 1.

In an example, taking the data source of the training sample data as the data source 3, in the pre-simulation process, for each training sample data, the downlink signal received by the detected terminal may be:

the downlink strong may refer to a strong interference cell, and the downlink weak may refer to a weak interference cell. Uplink strong may refer to strong interfering terminals. Uplink weak may refer to weak interfering terminals.

It should be noted that, the method for determining the strong interference terminal and the weak interference terminal may refer to the method for determining the strong interference cell and the weak interference cell, which are not described in detail.

In one example, for the above downlink signal, the following is noted In the training sample data, interference cancellation factor of the interfering terminal +.> q represents an element of the q-th row of C, and j represents an element of the j-th column of C.

Yet another kind ofIn an example, for the above downlink signal, note In the training sample data, interference elimination factor of interference terminal +.> q represents an element of the q-th row of C, and j represents an element of the j-th column of C.

S502, training a preset neural network algorithm on a plurality of sample training data to obtain a preset neural network model.

The preset neural network algorithm may be a back-propagation algorithm (BP) or a convolutional neural network (convolutional neural network, CNN). Of course, other neural network algorithms are also possible, without limitation.

The preset neural network model can be used for determining an interference elimination factor of an interference terminal. The input of the preset neural network model is the configuration information of the target terminal, the configuration information of the service cell, the configuration information of the interference cell and the configuration information of the interference terminal, and the input is the interference elimination factor of the interference terminal.

In one example, as shown in fig. 6, taking a preset neural network algorithm as an example of a BP algorithm, the BP algorithm may include an input layer, a plurality of intermediate layers, and an output layer.

Wherein the input layer may include n inputs (e.g., x 1-xn). Each input is for inputting a set of training sample data. And a plurality of intermediate layers (for example, n 1-ns) are used for carrying out iterative training on training sample data and transmitting training results to a value output layer. The output layer may include m outputs (e.g., y 1-ym), each for outputting a training result. n, m and s are positive integers.

Based on the above S501 and S502, in the pre-simulation stage, the configuration information of the detected user and the configuration information of the interfering user may be trained according to a preset neural network algorithm, so as to obtain a preset neural network model. In this way, in the subsequent simulation process, the interference elimination factor of the interference terminal can be determined according to the preset neural network model obtained in the stage, so that the simulation method is simple and convenient.

2. And (5) a simulation stage.

As shown in fig. 7, the present application provides a method for detecting a downlink signal of a flexible frame structure simulation system, where the method includes:

s701, determining the signal strength of a first downlink signal from a serving cell received by a target terminal.

Wherein the target terminal may be terminal 1 in fig. 2. The serving cell may be cell 1 in fig. 2.

In one example, the first downlink signal received by the target terminal from the serving cell may be that, in the simulation environment, the serving cell transmits the downlink signal to the target terminal in response to the input instruction. Accordingly, in the same simulation environment, the target terminal can receive the first downlink signal from the serving cell.

In the embodiment of the present application, the serving cell, the interfering cell, the target terminal and the interfering terminal are all in the same simulation environment. The interaction between cells and the interaction between the signals between the cells and the terminal are all the interaction of simulation analog signals. The signals between the serving cell and the target terminal and the signals between the interference cell and the interference terminal are analog signals. The analog signal may be generated for the emulation device in response to an input instruction. Thus, the simulation equipment can acquire the signals transmitted by each cell and each terminal and the received signals.

Further, since the target terminal needs to perform linear detection after receiving the downlink signal from the serving cell, the original downlink signal (i.e., the first downlink signal) can be obtained.

In an example, to obtain the original downlink signal, the simulation device may establish a channel matrix between the target terminal and the serving cell through simulation, and obtain a precoding matrix of the serving cell. Then, the simulation device may determine, according to the channel matrix between the target terminal and the serving cell and the precoding matrix of the serving cell, a signal when the downlink signal sent by the serving cell reaches the target terminal. Furthermore, the simulation device can perform linear detection on the signal to obtain a first downlink signal from the serving cell, which is received by the target terminal.

The method for establishing the channel matrix between the target terminal and the serving cell may refer to the prior art, and will not be described in detail. The precoding matrix of the serving cell may be preconfigured for the serving cell, the precoding matrix being related to the antenna configuration information of the serving cell. Alternatively, the precoding matrix of the serving cell may be configured for the serving cell through simulation.

For example, the signal when the downlink signal sent by the serving cell reaches the target terminal may beThe simulation device can perform linear detection on the signal according to a preset detection algorithm or a preset detection matrix to obtain a downlink signal from the serving cell received by the target terminal. For example, the linear matrix may be the detection matrix D described above. The downlink signal from the serving cell received by the target terminal is +>

Further, after obtaining the first downlink signal from the serving cell received by the target terminal, the simulation device may determine the signal strength of the first downlink signal according to the first downlink signal.

The signal strength of the first downlink signal satisfies the formula two.

S1＝P|DHW ₁ | ² Formula II

Wherein S1 is the signal strength of the first downlink signal from the serving cell received by the target terminal, P is the signal transmitting power of the serving cell, D is a preset detection matrix, and H is the signal between the serving cell and the target terminal Track matrix, W ₁ Is a precoding matrix of the serving cell.

S702, determining a first interference value of downlink signals of a plurality of interference cells to a first downlink signal and a second interference value of noise to the first downlink signal.

The interfering cell may be cell 2 in fig. 2. The plurality of interfering cells may be divided into strong interfering cells and weak interfering cells according to a large-scale path loss between the interfering cells and the target terminal. The strong interference cell and the weak interference cell may be referred to the above description, and will not be repeated. Noise may refer to interfering signals other than interfering cells and interfering terminals.

The first interference value may be a sum of an interference value of a downlink signal of the strong interference cell to the first downlink signal and an interference value of a downlink signal of the weak interference cell to the first downlink signal.

In an example, the simulation device may calculate an interference value of a downlink signal of the strong interference cell on the first downlink signal according to a signal transmitting power of the strong interference cell, a channel matrix between the target terminal and the strong interference cell, and a precoding matrix of the strong interference cell.

For example, the interference value of the downlink signal of the strong interference cell on the first downlink signal may satisfy the formula three.

Bq＝∑ _{i epsilon downlink strong} ∑ _j P _i |DH _1g W _i | ² Formula III

Wherein Bq represents an interference value of a downlink signal of a strong interference cell to the first downlink signal. P (P) _i Representing the signal transmit power of the strongly interfering cell. H _1g Representing the channel matrix between the strong interfering cell and the target terminal. i denotes the number of strong interfering cells. j represents the number of streams of the downlink signal of the strong interfering cell. i. j is a positive integer. W (W) _i Representing the precoding matrix of the strong interfering cell. i is a positive integer.

In yet another example, the simulation device may calculate an interference value of a downlink signal of the weak interference cell on the first downlink signal according to a signal transmission power of the weak interference cell and a link loss of the target terminal to the weak interference cell.

Wherein, the link loss L between the target terminal and the weak interference cell _ug ＝PL _ug -G _g -G _u 。PL _ug Representing a large scale path loss. G _g Indicating the antenna gain of the weak interfering cell. G _u Indicating the antenna gain of the target terminal. The method of calculating the antenna gain can be referred to the prior art.

For example, the interference value of the downlink signal of the weak interference cell on the first downlink signal may satisfy the fourth formula.

Br＝∑ _{i epsilon downlink weak} ∑ _j |D| ² P _w /L _ug Equation four

Wherein Br represents an interference value of a downlink signal of the weak interference cell to the first downlink signal. P (P) _w Representing the signal transmit power of the weak interfering cell. i denotes the number of weak interfering cells. j represents the number of streams of the downlink signal of the weak interfering cell. i. j is a positive integer. W (W) _i Representing the precoding matrix of the strong interfering cell. i is a positive integer.

When the number of strong interference cells and weak interference cells is plural, the interference value of the strong interference cells to the first downlink signal may be the sum of the interference values of the strong interference cells to the first downlink signal. The interference value of the weak interference cell to the first downlink signal may refer to a sum of interference values of the plurality of weak interference cells to the first downlink signal.

In yet another example, the second interference value of the noise on the first downlink signal may satisfy the formula five.

B2＝∑ _j |D| ² σ ² Formula five

Wherein B2 represents the second interference value. j represents the number of streams of noise.

S703, determining an interference elimination factor of the interference terminal according to a preset neural network model.

The pre-set neural network model may refer to the description in the pre-simulation stage.

In an example, the simulation device may input configuration information of a cell and a terminal related to the interfering terminal into a preset neural network model to obtain an interference cancellation factor of the interfering terminal. For example, cells and terminals associated with an interfering terminal may include a target terminal, a serving cell for the target terminal, an interfering terminal, and an interfering cell. The configuration information may include location information and/or antenna configuration information. For example, the configuration information of the target terminal may include antenna configuration parameters of the target terminal. The configuration information of the serving cell may include antenna location information. The configuration information of the interfering cell may include antenna location information. The configuration information of the interfering terminal may include location information of the interfering terminal and signal transmission power.

S704, determining a third interference value of the uplink signal of the interference terminal to the first downlink signal according to the interference cancellation factor of the interference terminal, the signal transmitting power of the interference terminal and the link loss between the interference terminal and the target terminal.

The uplink signal of the interfering terminal may refer to an uplink signal sent by the interfering terminal to a serving cell of the interfering terminal, where a time slot used by the interfering terminal to send the uplink signal is the same as a time slot used by the target terminal to send the first uplink signal. Link loss L between interfering terminal and target terminal _1i ＝PL _ui -G _g -G _i 。PL _ui Representing the large scale path loss between the target terminal and the interfering terminal. G _i Indicating the antenna gain of the interfering terminal.

In one example, the third interference value satisfies equation six.

B3＝∑ _{i epsilon uplink} ηP _i /L _1i Formula six

Wherein B3 represents a third interference value. η represents an interference cancellation factor. P (P) _i Representing the signal transmit power of the interfering terminal. i denotes the number of interfering terminals. i is a positive integer.

S705, determining the signal-to-noise ratio of the first downlink signal according to the signal strength of the first downlink signal, the first interference value, the second interference value and the third interference value.

Wherein the signal-to-noise ratio of the first downlink signal satisfies the formula seven.

SINR = S1/(s1+b1+b2+b3) equation seven

The SINR is the signal-to-noise ratio of the downlink signal received by the target terminal.

Based on the technical scheme shown in fig. 7, the embodiment of the application provides a downlink signal detection method of a flexible frame structure simulation system, when a serving cell adopts a flexible frame structure to send a downlink signal to a terminal, the downlink signal received by the terminal from the serving cell can be interfered by the downlink signal and the uplink signal of an adjacent cell. Based on this, in the embodiment of the present application, the signal to noise ratio of the downlink signal from the serving cell received by the terminal may be calculated according to the interference values of a plurality of interference sources (for example, the downlink signal of the interfering cell, the noise, the uplink signal of the interfering terminal, etc.) that generate interference to the downlink signal from the serving cell received by the terminal, so that the signal to noise ratio is comprehensive and accurate.

In a possible embodiment, as shown in fig. 8, an embodiment of the present application provides a method for detecting a downlink signal of a flexible frame structure simulation system, where the method may include S801 to S808.

S801, a channel matrix between a target terminal and a serving cell and a strong interference cell is established.

Herein, S801 may refer to the descriptions of S701 and S702, which are not described herein.

S802, calculating the link loss between the target terminal and the interference terminal.

Herein, S802 may refer to the description of S704, which is not described herein.

S803, determining the link loss between the target terminal and the weak interference cell.

Herein, S803 may refer to the description of S702, which is not described herein.

S804, determining whether the time slot used by the interference cell is an uplink time slot.

The time slot used by the interfering cell may refer to a time slot (e.g. D, S, U) in a flexible frame structure used by the interfering cell at the current time.

And S805, when the time slot used by the interference cell is an uplink time slot, using the terminal using the uplink time slot of the interference cell as an interference terminal.

Wherein the interfering terminals may also be referred to as cross-slot interfering terminals.

S806, determining an interference elimination factor of the interference terminal according to a preset neural network model.

Here, S806 may refer to the description of S703, which is not described herein.

S807, when the time slot used by the interference cell is not an uplink time slot, determining whether the target terminal establishes a channel matrix with the interference cell.

Wherein determining whether the target terminal establishes a channel matrix with the interfering cell may be used to determine whether the interference is a strong interfering cell.

Specifically, when the target terminal and the interference cell establish a channel matrix, the interference cell is used as a strong interference cell; and when the target terminal does not establish a channel matrix with the interference cell, the interference cell is used as a weak interference cell.

In the embodiment of the present application, when the simulation device starts to perform the simulation task, the large-scale path loss between the target terminal and the multiple interference cells may be calculated first, and the strong interference cells and the weak interference cells in the multiple interference cells may be determined according to the large-scale path loss between the target terminal and the multiple interference cells. The simulation device may then establish a channel matrix with the strongly interfering cells.

S808, calculating the signal to noise ratio of the downlink signal received by the target terminal according to the interference value of the strong interference cell, the interference value of the weak interference cell and the interference value of the interference terminal.

In S808, reference may be made to the technical solution of fig. 7, which is not described herein.

When the target terminal accesses a plurality of cells (including a serving cell and a plurality of interfering cells) in the simulation phase, the simulation device may perform steps S804 to S807 in a loop to determine a strong interfering cell and a weak interfering cell of the plurality of interfering cells.

Based on the technical scheme of fig. 8, for the cell adopting the flexible frame structure, the simulation device can accurately and comprehensively determine the signal-to-noise ratio of the downlink signal received by the terminal by calculating the interference values of the interference cell (including the strong interference cell and the weak interference cell) which generate interference to the downlink signal received by the terminal and the interference terminal (i.e. the cross time slot interference terminal). Furthermore, the simulation device can detect the downlink signal according to the signal-to-noise ratio of the downlink signal received by the terminal.

The various schemes in the embodiments of the present application may be combined on the premise of no contradiction.

According to the embodiment of the application, the downlink signal detection device of the flexible frame structure simulation system can be divided into the functional modules or the functional units according to the method example, for example, each functional module or each functional unit can be divided corresponding to each function, and two or more functions can be integrated into one processing module. The integrated modules may be implemented in hardware, or in software functional modules or functional units. The division of the modules or units in the embodiments of the present application is merely a logic function division, and other division manners may be implemented in practice.

In the case of dividing the respective functional modules with the respective functions, fig. 9 shows a schematic configuration of a downstream signal detection apparatus 90, which downstream signal detection apparatus 90 can be used to perform the functions involved in the simulation device in the above-described embodiment. The downstream signal detection device 90 shown in fig. 9 may include: a determining unit 901, a processing unit 902.

A determining unit 901, configured to determine a signal strength of a first downlink signal received by a target terminal, and determine a first interference value of downlink signals of a plurality of interfering cells to the first downlink signal and a second interference value of noise to the first downlink signal.

The processing unit 902 is configured to determine an interference cancellation factor of the interfering terminal according to a preset neural network algorithm, and calculate a third interference value of an uplink signal of the interfering terminal to the first downlink signal according to the interference cancellation factor of the interference, a signal transmitting power of the interfering terminal, and a link loss between the interfering terminal and the target terminal, where the uplink signal of the interfering terminal interferes with the first downlink signal, and the interference cancellation factor of the interfering terminal is used to characterize an interference degree of the uplink signal sent by the interfering terminal to the first signal.

The processing unit 902 is further configured to determine a signal-to-noise ratio of the first downlink signal according to the signal strength of the first downlink signal, the first interference value, the second interference value, and the third interference value.

In a possible implementation manner, the plurality of interference cells include a strong interference cell and a weak interference cell, the strong interference cell is an interference cell, in which a large-scale path loss between the plurality of interference cells and the target terminal is greater than or equal to a preset threshold, and the weak interference cell is an interference cell, in which a large-scale path loss between the plurality of interference cells and the target terminal is less than the preset threshold, and the determining unit 901 is specifically configured to: calculating the interference value of the downlink signal of the strong interference cell on the first downlink signal according to the signal transmitting power of the strong interference cell, the channel matrix between the target terminal and the strong interference cell and the precoding matrix of the strong interference cell; according to the signal transmitting power of the weak interference cell and the link loss from the target terminal to the weak interference cell, calculating the interference value of the downlink signal of the weak interference cell on the first downlink signal, wherein the first interference value comprises: the interference value of the downlink signal of the strong interference cell to the downlink signal of the service cell and the interference value of the downlink signal of the weak interference cell to the downlink signal of the service cell.

In a possible implementation manner, the processing unit 902 is specifically configured to: acquiring configuration information of a target terminal, configuration information of a serving cell, configuration information of an interference cell and configuration information of an interference terminal, wherein the configuration information comprises antenna configuration information and/or position information; and inputting the configuration information of the target terminal, the configuration information of the serving cell, the configuration information of the interference cell and the configuration information of the interference terminal into a preset neural network model to obtain an interference elimination factor.

In a possible implementation manner, the determining unit 901 is further configured to calculate, through simulation, an antenna gain of the target terminal and an antenna gain of the interference terminal, and determine a large-scale path loss between the target terminal and the interference terminal; the processing unit 902 is further configured to determine a link loss between the target terminal and the interfering terminal according to the difference between the large-scale path loss and the antenna gain of the target terminal and the antenna gain of the interfering terminal.

In a possible implementation manner, as shown in fig. 9, the downlink signal detection apparatus further includes an establishing unit 903, configured to establish a channel matrix between the target terminal and the serving cell through simulation; the processing unit 902 is configured to determine a signal when a downlink signal sent by a serving cell reaches a target terminal according to a signal transmitting power of the serving cell, a channel matrix between the target terminal and the serving cell, and a precoding matrix of the serving cell, and perform linear detection on the signal when the downlink signal sent by the serving cell reaches the target terminal based on a preset detection algorithm, so as to obtain a first downlink signal.

In a possible implementation manner, the signal strength of the first downlink signal satisfies a first formula, where the first formula is: s1=p|dhw| ² The method comprises the steps of carrying out a first treatment on the surface of the Wherein S1 is the signal strength of the downlink signal, P is the signal transmitting power of the serving cell, D is a preset detection matrix, H is a channel matrix between the serving cell and the target terminal, and W is a precoding matrix of the serving cell.

In one possible implementation, the signal-to-noise ratio satisfies a second formula, where the second formula is: sinr=s1/(s1+b1+b2+b3); wherein, SINR is the signal-to-noise ratio of the first downlink signal, S1 is the signal strength of the first downlink signal, B1 is the first interference value, B2 is the second interference value, and B3 is the third interference value.

As yet another implementation, the processing unit 902 in fig. 9 may be replaced by a processor, which may integrate the functionality of the processing unit 902.

Further, when the processing unit 902 is replaced by a processor, the downlink signal detecting apparatus 90 according to the embodiments of the present application may be a downlink signal detecting apparatus shown in fig. 3.

Embodiments of the present application also provide a computer-readable storage medium. All or part of the flow in the above method embodiments may be implemented by a computer program to instruct related hardware, where the program may be stored in the above computer readable storage medium, and when the program is executed, the program may include the flow in the above method embodiments. The computer readable storage medium may be an internal storage unit of the downlink signal detecting apparatus (including the data transmitting end and/or the data receiving end) of any of the foregoing embodiments, such as a hard disk or a memory of the downlink signal detecting apparatus. The computer readable storage medium may be an external storage device of the terminal apparatus, for example, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, a flash card (flash card), or the like, which are provided in the terminal apparatus. Further, the above-mentioned computer readable storage medium may further include both the internal storage unit and the external storage device of the above-mentioned downstream signal detection apparatus. The computer-readable storage medium stores the computer program and other programs and data required by the downstream signal detection device. The above-described computer-readable storage medium may also be used to temporarily store data that has been output or is to be output.

It should be noted that the terms "first" and "second" and the like in the description, claims and drawings of the present application are used for distinguishing between different objects and not for describing a particular sequential order. Furthermore, the terms "comprise" and "have," as well as any variations thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those listed steps or elements but may include other steps or elements not listed or inherent to such process, method, article, or apparatus.

It should be understood that, in the present application, "at least one (item)" means one or more, "a plurality" means two or more, "at least two (items)" means two or three and three or more, "and/or" for describing an association relationship of an association object, three kinds of relationships may exist, for example, "a and/or B" may mean: only a, only B and both a and B are present, wherein a, B may be singular or plural. The character "/" generally indicates that the context-dependent object is an "or" relationship. "at least one of" or the like means any combination of these items, including any combination of single item(s) or plural items(s). For example, at least one (one) of a, b or c may represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", wherein a, b, c may be single or plural.

From the foregoing description of the embodiments, it will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of functional modules is illustrated, and in practical application, the above-described functional allocation may be implemented by different functional modules according to needs, i.e. the internal structure of the apparatus is divided into different functional modules to implement all or part of the functions described above.

In the several embodiments provided in this application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of the modules or units is merely a logical functional division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another apparatus, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.

The units described as separate parts may or may not be physically separate, and the parts displayed as units may be one physical unit or a plurality of physical units, may be located in one place, or may be distributed in a plurality of different places. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in each embodiment of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.

The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a readable storage medium. Based on such understanding, the technical solution of the embodiments of the present application may be essentially or a part contributing to the prior art or all or part of the technical solution may be embodied in the form of a software product stored in a storage medium, including several instructions for causing a device (may be a single-chip microcomputer, a chip or the like) or a processor (processor) to perform all or part of the steps of the methods described in the embodiments of the present application. And the aforementioned storage medium includes: a usb disk, a removable hard disk, a ROM, a RAM, a magnetic disk, or an optical disk, etc.

The foregoing is merely a specific embodiment of the present application, but the protection scope of the present application is not limited thereto, and any changes or substitutions within the technical scope of the present disclosure should be covered in the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. The downlink signal detection method of a flexible frame structure simulation system is characterized in that the flexible frame structure simulation system comprises a serving cell of a target terminal and a plurality of interference cells, and the method comprises the following steps:

determining the signal strength of a first downlink signal received by the target terminal;

determining first interference values of downlink signals of the plurality of interference cells to the first downlink signals and second interference values of noise to the first downlink signals;

determining an interference elimination factor of an interference terminal according to a preset neural network algorithm, and calculating third interference of an uplink signal of the interference terminal to the first downlink signal according to the interference elimination factor of the interference terminal, the signal transmitting power of the interference terminal and the link loss between the interference terminal and the target terminalThe value is that the interference terminal generates interference to the first downlink signal by the uplink signal transmitted by the interference terminal, and the interference cancellation factor of the interference terminal is used for representing the interference degree of the uplink signal transmitted by the interference terminal to the first downlink signal; the third interference value = Σ _{i epsilon uplink} ηP _i /L _1i The method comprises the steps of carrying out a first treatment on the surface of the η represents the interference cancellation factor, P _i Representing the signal transmission power of an interfering terminal, L _1i The link loss between the interference terminal and the target terminal is represented, i represents the number of the interference terminals, and i is a positive integer;

wherein, the determining the interference cancellation factor of the interference terminal according to a preset neural network algorithm includes: acquiring configuration information of the target terminal, configuration information of the service cell, configuration information of the interference cell and configuration information of the interference terminal, wherein the configuration information comprises antenna configuration information and/or position information; inputting the configuration information of the target terminal, the configuration information of the service cell, the configuration information of the interference cell and the configuration information of the interference terminal into a preset neural network model to obtain the interference cancellation factor;

and determining the signal-to-noise ratio of the first downlink signal according to the signal strength of the first downlink signal, the first interference value, the second interference value and the third interference value.

2. The method according to claim 1, wherein the plurality of interfering cells includes a strong interfering cell and a weak interfering cell, the strong interfering cell being an interfering cell in which a large-scale path loss between the plurality of interfering cells and the target terminal is greater than or equal to a preset threshold, the weak interfering cell being an interfering cell in which a large-scale path loss between the plurality of interfering cells and the target terminal is less than the preset threshold, the determining a first interference value of a downlink signal of the plurality of interfering cells to a downlink signal of the target terminal includes:

Calculating the interference value of the downlink signal of the strong interference cell to the first downlink signal according to the signal transmitting power of the strong interference cell, the channel matrix between the target terminal and the strong interference cell and the precoding matrix of the strong interference cell;

according to the signal transmitting power of the weak interference cell and the link loss from the target terminal to the weak interference cell, calculating the interference value of the downlink signal of the weak interference cell on the first downlink signal, wherein the first interference value comprises: the interference value of the downlink signal of the strong interference cell to the downlink signal of the service cell and the interference value of the downlink signal of the weak interference cell to the downlink signal of the service cell.

3. The method according to claim 1 or 2, characterized in that the method further comprises:

calculating the antenna gain of the target terminal and the antenna gain of the interference terminal through simulation, and determining the large-scale path loss between the target terminal and the interference terminal;

and determining the link loss between the target terminal and the interference terminal according to the large-scale path loss and the difference between the antenna gain of the target terminal and the antenna gain of the interference terminal.

4. The method according to claim 1, wherein the method further comprises:

establishing a channel matrix between the target terminal and the service cell through simulation;

determining a signal when a downlink signal sent by the serving cell reaches the target terminal according to the signal transmitting power of the serving cell, a channel matrix between the target terminal and the serving cell and a precoding matrix of the serving cell;

and based on a preset detection algorithm, linearly detecting a signal when the downlink signal sent by the service cell reaches the target terminal to obtain the first downlink signal.

5. The method of claim 4, wherein the signal strength of the first downlink signal satisfies a first formula:

S1＝P|DHW| ² ；

wherein S1 is the signal strength of the first downlink signal, P is the signal transmitting power of the serving cell, D is a preset detection matrix, H is a channel matrix between the serving cell and the target terminal, and W is a precoding matrix of the serving cell.

6. The method of claim 1, wherein the signal-to-noise ratio satisfies a second formula, the second formula being:

SINR＝S1/(S1+B1+B2+B3)；

Wherein SINR is a signal-to-noise ratio of the first downlink signal, S1 is a signal strength of the first downlink signal, B1 is the first interference value, B2 is the second interference value, and B3 is the third interference value.

7. The downlink signal detection device of the flexible frame structure simulation system is characterized in that the flexible frame structure simulation system comprises a serving cell of a target terminal and a plurality of interference cells, and the device comprises a determination unit and a processing unit;

the determining unit is used for determining the signal strength of the first downlink signal received by the target terminal;

the determining unit is further configured to determine a first interference value of the downlink signals of the plurality of interfering cells on the first downlink signal and a second interference value of noise on the first downlink signal;

the processing unit is configured to determine an interference cancellation factor of an interfering terminal according to a preset neural network algorithm, calculate a third interference value of an uplink signal of the interfering terminal to the first downlink signal according to the interference cancellation factor of the interfering terminal, a signal transmitting power of the interfering terminal, and a link loss between the interfering terminal and the target terminal, where the interfering terminal is a terminal that generates interference to the first downlink signal by a transmitted uplink signal, and the interfering terminal The interference cancellation factor of (a) is used for representing the interference degree of the uplink signal sent by the interference terminal to the first downlink signal; the third interference value = Σ _{i epsilon uplink} ηP _i /L _1i The method comprises the steps of carrying out a first treatment on the surface of the η represents the interference cancellation factor, P _i Representing the signal transmission power of an interfering terminal, L _1i The link loss between the interference terminal and the target terminal is represented, i represents the number of the interference terminals, and i is a positive integer;

the processing unit is specifically configured to obtain configuration information of the target terminal, configuration information of the serving cell, configuration information of the interfering cell, and configuration information of the interfering terminal, where the configuration information includes antenna configuration information and/or location information; inputting the configuration information of the target terminal, the configuration information of the service cell, the configuration information of the interference cell and the configuration information of the interference terminal into a preset neural network model to obtain the interference cancellation factor;

8. The apparatus according to claim 7, wherein the plurality of interfering cells includes a strong interfering cell and a weak interfering cell, the strong interfering cell being an interfering cell in which a large-scale path loss between the plurality of interfering cells and the target terminal is greater than or equal to a preset threshold, the weak interfering cell being an interfering cell in which a large-scale path loss between the plurality of interfering cells and the target terminal is less than the preset threshold, the determining unit being specifically configured to:

9. The apparatus according to claim 7 or 8, wherein,

the determining unit is further configured to calculate, through simulation, an antenna gain of the target terminal and an antenna gain of the interference terminal, and determine a large-scale path loss between the target terminal and the interference terminal;

the determining unit is further configured to determine a link loss between the target terminal and the interfering terminal according to the large-scale path loss and a difference between an antenna gain of the target terminal and an antenna gain of the interfering terminal.

10. The apparatus according to claim 7, characterized in that the apparatus further comprises a setup unit:

the establishing unit is used for establishing a channel matrix between the target terminal and the service cell through simulation;

the determining unit is further configured to determine a signal when a downlink signal sent by the serving cell reaches the target terminal according to the signal transmitting power of the serving cell, a channel matrix between the target terminal and the serving cell, and a precoding matrix of the serving cell;

the processing unit is further configured to perform linear detection on a signal when the downlink signal sent by the serving cell reaches the target terminal based on a preset detection algorithm, so as to obtain the first downlink signal.

11. The apparatus of claim 10, wherein the signal strength of the first downlink signal satisfies a first formula:

S1＝P|DHW| ² ；

12. The apparatus of claim 7, wherein the signal-to-noise ratio satisfies a second formula, the second formula being:

SUNR＝S1/(S1+B1+B2+B3)；

13. A computer readable storage medium having instructions stored therein which, when executed, implement the method of any of claims 1-6.

14. A signal detection apparatus, comprising: a processor, a memory, and a communication interface; wherein the communication interface is used for the signal detection device to communicate with other equipment or network; the memory is configured to store one or more programs, the one or more programs comprising computer-executable instructions that, when executed by the signal detection apparatus, cause the signal detection apparatus to perform the method of any of claims 1-6.