CN115087011A

CN115087011A - Downlink signal detection method and device of flexible frame structure simulation system

Info

Publication number: CN115087011A
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: 2022-09-20
Anticipated expiration: 2042-06-20
Also published as: CN115087011B

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 includes a serving cell and an interfering cell of a 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 to the first downlink signal and a second interference value of noise to the first downlink signal; determining an interference elimination factor of an interference terminal according to a preset neural network algorithm, and calculating a third interference value of the interference uplink signal to the first downlink signal according to the interference elimination factor, the signal transmission power of the interference terminal and the 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

Downlink signal detection method and device 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 (TDD) mode, a cell may use different time slots of the same frequency channel (i.e., carrier) to achieve transmission and reception of signals. Also, the cells may allocate uplink and downlink of the communication system to the same frequency spectrum by using TDD technology. The uplink and downlink respectively occupy different time periods, so that the 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, for example, DSUUU, DDSUU, and DDDSU. Where D denotes a Downlink slot (Downlink slot) refers to a slot for Downlink transmission. S denotes a Special slot (Special slot) which refers to a slot for downlink transmission or uplink transmission. U denotes an Uplink slot (Uplink slot) which refers to a slot for Uplink transmission. Therefore, the cell can flexibly select proper subframe structure configuration according to the uplink and downlink traffic volume born by the cell, thereby using the uplink and downlink bandwidth configured by the subframe structure to transmit the service. However, when different cells use different subframe configuration structures to transmit downlink signals to the terminal, the downlink signals received by the terminal may suffer from cross slot interference. At this time, it is necessary to detect the downlink signal received by the terminal to determine the signal quality of the downlink signal.

Disclosure of Invention

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

In order to achieve the purpose, the technical scheme is as follows:

in a first aspect, a method for detecting a downlink signal of a flexible frame structure simulation system is provided, where the flexible frame structure simulation system includes a serving cell of a target terminal and multiple interfering cells, and the method includes: determining the signal strength of a first downlink signal received by a target terminal, and determining first interference values of the downlink signals of a plurality of interference cells to the first downlink signal and second interference values of noise to the first downlink signal; determining an interference elimination factor of an interference terminal according to a preset neural network algorithm, 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 generates interference to 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 serving cell adopts a flexible frame structure to send the downlink signal to the terminal, the downlink signal from the serving 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 interference values (which may also be referred to as interference powers) of a plurality of interference sources (for example, the downlink signal of the interfering cell, noise, the uplink signal of the interfering terminal, and the like) which generate interference on the downlink signal from the serving cell received by the terminal. The signal-to-noise ratio of the signal can reflect the signal quality of the signal, so 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 multiple interfering cells include a strong interfering cell and a weak interfering cell, the strong interfering cell is an interfering cell in which a large-scale path loss between the multiple interfering cells and the target terminal is greater than or equal to a preset threshold, the weak interfering cell is an interfering cell in which a large-scale path loss between the multiple interfering cells and the target terminal is less than the preset threshold, and the determining a first interference value of downlink signals of the multiple interfering cells to a downlink signal of the target terminal includes: calculating an interference value of a downlink signal of the strong interference cell to the first downlink signal according to the 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; calculating an interference value of a downlink signal of the weak interference cell to a first downlink signal according to the signal transmitting power of the weak interference cell and the link loss from the target terminal to the weak interference cell, wherein the first interference value comprises: the interference value of the downlink signal of the strong interference cell to the downlink signal of the serving cell and the interference value of the downlink signal of the weak interference cell to the downlink signal of the serving 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 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 an interference elimination factor.

In a possible implementation, the method further includes: calculating the antenna gain of a target terminal and the antenna gain of an 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 value between the antenna gain of the target terminal and the antenna gain of the interference terminal.

In a possible implementation, 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 performing linear detection on a signal when a downlink signal sent by the serving cell reaches the target terminal based on a preset detection algorithm to obtain a first downlink signal.

In one possible implementation manner, the signal strength of the first downlink signal satisfies a first formula, where the first formula is: s1 ═ P | DHW- ² (ii) a Wherein S1 is the signal strength of the first downlink signal, P is the signal transmission power of the serving cell, D is the preset detection matrix, H is the channel matrix between the serving cell and the target terminal, and W is the serving cellA precoding matrix of the region.

In one possible implementation manner, the snr of the first downlink signal satisfies a second formula, where the second formula is: SINR is 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 a first interference value, B2 is a second interference value, and B3 is a 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 of a target terminal and multiple interfering cells, and the downlink signal detection apparatus may be a functional module configured to implement the method according to the first aspect or any possible design of the first aspect. The downlink signal detection apparatus may implement the functions performed in the above aspects or possible designs, and 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.

The determining unit is configured to determine the signal strength of the first downlink signal received by the target terminal, and determine first interference values of the downlink signals of the multiple interfering cells to the first downlink signal and second interference values of the noise to 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 generates interference to 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 the processing unit is further used for 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.

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

In a possible implementation manner, the multiple interfering cells include a strong interfering cell and a weak interfering cell, the strong interfering cell is an interfering cell in which a large-scale path loss between the multiple interfering cells and a target terminal is greater than or equal to a preset threshold, and the weak interfering cell is an interfering cell in which a large-scale path loss between the multiple interfering cells and the target terminal is less than the preset threshold, and the determining unit is specifically configured to: calculating an interference value of a downlink signal of the strong interference cell to the first downlink signal according to the 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; calculating an interference value of a downlink signal of the weak interference cell to a first downlink signal according to the signal transmitting power of the weak interference cell and the link loss from the target terminal to the weak interference cell, wherein the first interference value comprises: the interference value of the downlink signal of the strong interference cell to the downlink signal of the serving cell and the interference value of the downlink signal of the weak interference cell to the downlink signal of the serving 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 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 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 interfering terminal, and determine a large-scale path loss between the target terminal and the interfering terminal; and the processing unit is further used for determining the link loss between the target terminal and the interference terminal according to the large-scale path loss and the difference value between the antenna gain of the target terminal and the antenna gain of the interference terminal.

In a possible implementation manner, the downlink signal detection apparatus further includes an establishing unit, configured to establish a channel matrix between the target terminal and the serving cell through simulation; and the processing unit is used for determining a 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 performing 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 one possible implementation manner, the signal strength of the first downlink signal satisfies a first formula, where the first formula is: s1 ═ P | DHW- ² (ii) a Wherein S1 is the signal strength of the downlink signal, P is the signal transmission 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 downlink signal detection apparatus (hereinafter, for convenience of description, simply referred to as a downlink signal detection apparatus) of a flexible frame structure simulation system is provided. The downlink signal detecting apparatus may implement the functions performed in the above aspects or in each possible design, and the functions may be implemented by hardware, such as: in one possible design, the downlink signal detecting apparatus may include: a processor and a communication interface, the processor being adapted to support the downstream signal detection apparatus to implement the functions referred to 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 apparatus may further include a memory for storing necessary computer-executable instructions and data for the downstream signal detection apparatus. When the downlink signal detection apparatus is running, the processor executes the computer-executable instructions stored in the memory, so that the downlink signal detection apparatus executes the method for detecting downlink signals of the flexible frame structure simulation system according to the first aspect or any one of the possible designs of the first aspect.

In a fourth aspect, a computer-readable storage medium is provided, which may be a readable non-volatile storage medium, and the computer-readable storage medium stores a computer instruction or a program, which when executed on a computer, enables the computer to execute the downlink signal detection method of the flexible frame structure simulation system according to the first aspect or any one of the possible designs of the above aspects.

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

A sixth aspect provides a chip system, where the chip system includes a processor and a communication interface, and the chip system may be configured to implement a function executed by the downlink signal detection apparatus of the flexible frame structure simulation system in the first aspect or any possible design of the first aspect, for example, where the processor is configured to determine a signal strength of a first downlink signal received by a target terminal. In one possible design, the system-on-chip further includes a memory to hold program instructions and/or data. The chip system may be formed by a chip, and may also include a chip and other discrete devices, without limitation.

The technical effects brought by any one of the design manners of the second aspect to the sixth aspect can be referred to the technical effects brought by the first aspect, and are not described in detail.

Drawings

Fig. 1 is a schematic structural diagram of another communication system provided in 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 disclosure;

fig. 4 is a schematic flowchart of a downlink signal detection method according to an embodiment of the present application;

fig. 5 is a schematic flowchart of a training method for a neural network model according to an embodiment of the present disclosure;

fig. 6 is a schematic structural diagram of a neural network provided in 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 make the technical solutions of the present disclosure better understood by those of ordinary skill in the art, 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 this application and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the disclosure described herein are capable of operation in sequences other than those illustrated or otherwise described herein. The implementations described in the exemplary embodiments below are not intended to represent all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the embodiments of the application, as detailed in the appended 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 cell can bring the maximum throughput gain, before the actual networking, the communication quality of the planned communication system can be evaluated and analyzed in a simulation mode. For example, for a New Radio (NR) cell in a communication system with a TDD model, the NR cell transmits data using a millimeter wave frequency band. However, the penetration performance of the millimeter wave frequency band is poor, and under the environment with good isolation, the NR cell may transmit data in a flexible frame manner using bandwidths corresponding to different subframe configuration structures. However, when the NR cell performs signal transmission with the terminal in a flexible frame manner, 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 can be determined by the signal-to-noise ratio. For example, the data throughput of the terminal can be calculated by mapping the block error rate of the downlink signal according to the signal-to-noise ratio. Therefore, in order to evaluate the network quality of the communication system, before networking, simulation may be performed to determine the signal-to-noise ratio of the downlink signal received by the terminal.

In a simulation scenario, when a cell and a terminal use a same-frame structure for signal transmission, a downlink signal sent by the cell to the terminal may be interfered by a downlink signal sent by an interfering cell in a same time slot. When a downlink signal from a certain detected cell (subsequently, the detected cell is referred to as a serving cell for distinguishing from an interfering cell) to a target terminal is received, the downlink signal from the serving cell received by the target terminal may be calculated according to the following formula i.

Where y represents a signal when a downlink signal transmitted by the serving cell reaches the target terminal. P ₁ And the signal transmitting power used when the serving cell sends a downlink signal to the target terminal is represented. H _1s Representing the channel matrix between the target terminal and the serving cell. The order of the channel matrix is Np × Nb. The elements in the channel matrix represent the frequency domain channel response between the antenna of the target terminal and the antenna 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 ₁ A precoding matrix representing a serving cell. The order of the precoding matrix is Nb × M1. M1 is the number of signal streams of the downstream signal. x is the number of ₁ ＝(x _1.1 ，x _1.2 ，…，x _1.M ) ^T And the normalized vector of the useful signal transmitted by the target terminal. P _i And the signal transmission power used when the strong interference cell sends the downlink signal is represented. H _1g Representing the channel matrix between the target terminal and the strong interfering cell. W _i A precoding matrix representing a strong interfering cell. x is the number of _i ＝(x ₁ ，x ₂ ，…，x _Mj ) ^T A normalized vector representing the signal transmitted by the interfering terminal. z is noise, z ═ z (z) ₁ ，z ₂ ，…，z _Nr ) ^T . The elements in z are independently identically distributed CN (0, sigma) ² )。σ ² Is the variance of the noise. P _w Representing the signal transmit power of the weak interfering cell. L is a radical of an alcohol _ig Representing 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 is not described in detail.

It should be noted that the interfering terminal may refer to a terminal that generates interference on 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 service for terminal 1, and cell 2 may provide communication service 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 to transmit the downlink signal to the same time slot, the downlink signal transmitted from the cell 2 to the terminal 2 may interfere with the downlink signal transmitted from the cell 1 to the terminal 1. At this time, cell 2 may be referred to as an interfering cell for cell 1 and 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 from 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.

Or, if the terminal 1 has multiple interfering cells, the sequencing may be performed according to the large-scale path loss from the multiple interfering cells to the terminal 1, and the first N interfering cells are used as strong interfering cells of the terminal 1, and the remaining interfering cells are 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, in order to reduce distortion of the signal and reduce the combined effect of inter-symbol interference (ISI) and noise on the signal. A signal receiving end (e.g., a 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 (MMSE), etc., and of course, may also 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 downlink signal is:

wherein the content of the first and second substances,

which represents a downlink signal received by a target terminal, and the downlink signal comprises a useful signal and an inter-stream interference signal.

Representing the interference signals of other terminals in the group of multi-user (MU) paired terminals and the interference signals of strong interfering cells. The MU pairing terminal group comprises a target terminal and one or more interference terminals of the target terminal. Dz represents noise interference.

Representing the interfering signal of a weak interfering cell.

For convenience of description, the detected downlink signal may be transformed into:

wherein the content of the first and second substances,

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

wherein A is _m Is the mth row element of a. B is _im Is B _i Row m elements of (1).

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

wherein A is _mj Row m and column j of a. B is _imj Is B _i Row m and column j. D _mj Row m and column j of D.

In another simulation scenario, when a cell and a terminal use a flexible frame structure for signal transmission, a downlink signal sent by the cell is interfered by not only a downlink signal of an interfering cell in a same time slot, but also an uplink signal of the interfering terminal.

For example, as shown in fig. 2, when the interfering terminal transmits an uplink signal to the interfering cell, the uplink signal may be received by the serving cell. When the time slot resources used by the interfering cell and the target terminal are the same, the uplink signal interferes with the downlink signal received by the target terminal. Meanwhile, the uplink signal sent by the interfering cell to the interfering terminal may also interfere with the downlink signal sent by the serving cell.

In view of this, an embodiment of the present application provides a method for detecting a downlink signal of a flexible frame structure simulation system, where when a serving cell sends a downlink signal to a terminal by using a flexible frame structure, the downlink signal received by the terminal from the serving cell may be interfered by a downlink signal and an 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 interference values (which may also be referred to as interference powers) of a plurality of interference sources (for example, the downlink signal from the interfering cell, noise, and the uplink signal from the interfering terminal) that generate interference with the downlink signal from the serving cell received by the terminal. The signal-to-noise ratio of the signal can reflect the signal quality of the signal, so 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 2 are both communication systems constructed by simulation equipment through simulation. The cells and the terminals in fig. 1 and 2 are in the same simulation system. The method in the embodiment of the application simulates the actual communication environment so as to obtain the signal-to-noise ratio of the downlink signal of the cell. Therefore, when networking is carried out subsequently, communication engineering personnel can adjust or optimize the cell to be planned according to the simulation result.

The method provided by the embodiment of the application is described in detail below with reference to the attached drawings.

It should be noted that the network system described in the embodiment of the present application is for more clearly illustrating the technical solution of the embodiment of the present application, and does not constitute a limitation to the technical solution provided in the embodiment of the present application, and as a person having ordinary skill in the art knows that along with the evolution of the network system and the appearance of other network systems, the technical solution provided in the embodiment of the present application is also applicable to similar technical problems.

In an example, an embodiment of the present application further provides a downlink signal detection apparatus (hereinafter, for convenience of description, simply referred to as a signal detection apparatus) of a flexible frame structure simulation system, where the signal detection apparatus may be used to execute 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 a simulation device. The downstream signal detection means may be provided with simulation software which may be used to perform a 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 apparatus 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, a general-purpose processor, a Network Processor (NP), a Digital Signal Processor (DSP), a microprocessor, a microcontroller, a Programmable Logic Device (PLD), or any combination thereof. The processor 301 may also be other devices with 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 respective components included in the downstream signal detection apparatus 300 of the flexible frame structure simulation system.

A memory 304 for storing instructions. Wherein the instructions may be a computer program.

The memory 304 may be a read-only memory (ROM) or other types of static storage devices that can store static information and/or instructions, a Random Access Memory (RAM) or other types of dynamic storage devices that can store information and/or instructions, an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compact disc, laser disc, optical disc, digital versatile disc, blu-ray disc, etc.), a magnetic disc storage medium or other magnetic storage devices, and the like, without limitation.

It is noted that the memory 304 may exist separately from the processor 301 or may be integrated with the processor 301. The memory 304 may be used for storing instructions or program code or some data or the like. The memory 304 may be located inside 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, which is not limited. The processor 301 is configured to execute the instructions stored in the memory 304 to implement the method for detecting a downlink signal of the flexible frame structure simulation system according to the following embodiments of the present application.

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

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

As an alternative implementation manner, 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-like device, and the output device 305 is a display screen, speaker (spaker), or like device.

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 with a similar structure as that 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 a combination of some components, or a different arrangement of components, in addition to those shown in fig. 3.

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

In addition, acts, terms, and the like referred to between the embodiments of the present application may be mutually referenced and are not limited. In the embodiment of the present application, the name of the message exchanged between the devices or the name of the parameter in the message, etc. are only an example, and other names may also be used in the specific implementation, which is not limited.

It should be noted that in the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described herein as "exemplary" or "e.g.," is not necessarily to be construed as preferred or advantageous over other embodiments or designs. Rather, use of the word "exemplary" or "such as" is intended to present relevant concepts in a concrete fashion.

In the present application, "at least one" means one or more, "a plurality" means two or more. "and/or" describes the association relationship of the associated objects, meaning that there may be three relationships, e.g., a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone, wherein A and B can be singular or plural. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship. "at least one of the following" or similar expressions refer to any combination of these items, including any combination of the singular or plural items. 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 multiple.

The method for detecting a downlink signal of the flexible frame structure simulation system according to the embodiment of the present application is described below with reference to the network architecture shown in fig. 2.

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

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

Firstly, a pre-simulation stage is carried out,

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

S501, obtaining a plurality of training sample data.

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

Wherein each training sample data may include configuration information of a detected user and configuration information of an interfering user. For example, the configuration information of the detected user may include antenna configuration parameters (such as the number of arrays, the number of channels, and antenna position information) of the detected terminal, and antenna position information of the serving cell of the detected terminal. The configuration information of the interfering user may include antenna position information of the interfering cell, position information and signal transmission power of the interfering terminal, and an interference cancellation factor of the interfering terminal. The interference elimination factor of the interfering terminal may reflect the degree of interference 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 a data source of training sample data as the data source 3 as an example, in the pre-simulation process, for each training sample data, the downlink signal received by the detected terminal may be:

the downlink strength may refer to a strong interference cell, and the downlink strength may refer to a weak interference cell. The uplink strong may refer to a strong interference terminal. The uplink weak may refer to a weak interfering terminal.

It should be noted that, the determination method of the strong interference terminal and the weak interference terminal may refer to the determination method of the strong interference cell and the weak interference cell, which is not described in detail.

In one example, for the downlink signal, note is made

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.

In another example, for the downlink signal, note is made

Interference elimination factor of interference terminal in the training sample data

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

The preset neural network algorithm may be a back-propagation (BP) algorithm or a 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 the interfering terminal. The input of the preset neural network model is configuration information of a target terminal, configuration information of a service cell, configuration information of an interference cell and configuration information of an interference terminal, and the output is an interference elimination factor of the interference terminal.

In one example, as shown in fig. 6, taking a preset neural network algorithm as the 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 input terminals (e.g., x 1-xn). Each input terminal 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 the training sample data and outputting the transmission value of the training result to the layers. 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. Therefore, in the subsequent simulation process, the interference elimination factor of the interference terminal can be determined according to the preset neural network model obtained at the stage, and the method is simple and convenient.

And II, 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 a downlink signal sent by the serving cell to the target terminal in response to an input instruction in the simulation environment. Accordingly, in the same simulation environment, the target terminal can receive the first downlink signal from the serving cell.

It should be noted that, 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 signals between the cells and the terminal are the interaction of simulation signals. Signals between the serving cell and the target terminal and signals between the interfering cell and the interfering terminal are analog signals. The analog signal may be generated by the emulation device in response to an input command. In this way, the simulation device can acquire the signals sent by each cell and each terminal and the received signals.

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

In an example, to obtain an 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 a channel matrix between the target terminal and the serving cell and a precoding matrix of the serving cell, a signal when a downlink signal transmitted by the serving cell reaches the target terminal. Furthermore, the simulation device may perform linear detection on the signal to obtain a first downlink signal from the serving cell 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 is not described in detail herein. The precoding matrix of the serving cell may be preconfigured for the serving cell, the precoding matrix being related to 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 transmitted by the serving cell reaches the target terminal may be

The simulation device may 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 intensity of the first downlink signal satisfies a formula two.

S1＝P|DHW ₁ | ² Formula two

Wherein, S1 is the signal strength of the first downlink signal from the serving cell received by the target terminal, P is the signal transmission 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 the channel matrix between the serving cell and the target terminal ₁ Is the 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 multiple interfering cells can be divided into strong interfering cells and weak interfering cells according to the large-scale path loss between the interfering cells and the target terminal. The strong interfering cell and the weak interfering cell may refer to the above description, and are not described in detail. The noise may refer to an interference signal other than the interfering cell and the interfering terminal.

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

In an example, the simulation device may calculate an interference value of the downlink signal of the strong interference cell to the first downlink signal according to the signal transmission 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.

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

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

Wherein, Bq represents the interference value of the downlink signal of the strong interference cell to the first downlink signal. P _i Representing the signal transmit power of a strong 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 _i A precoding matrix representing a strong interfering cell. i is a positive integer.

In another example, the simulation device may calculate an interference value of the downlink signal of the weak interfering cell to the first downlink signal according to the signal transmission power of the weak interfering cell and the link loss from the target terminal to the weak interfering 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 large scale path loss. G _g Indicating the antenna gain of the weak interfering cell. G _u Representing the antenna gain of the target terminal. The calculation method of the antenna gain can refer to the prior art.

For example, the interference value of the downlink signal of the weak interfering cell to the first downlink signal may satisfy formula four.

Br＝∑ _{i is e.e. downlink weak} ∑ _j |D| ² P _w /L _ug Formula four

And Br represents the interference value of the downlink signal of the weak interference cell to the first downlink signal. P is _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 _i A precoding matrix representing a strong interfering cell. i is a positive integer.

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

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

B2＝∑ _j |D| ² σ ² Formula five

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

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

The preset neural network model may refer to the description in the pre-simulation phase.

In one 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, the cells and terminals associated with the interfering terminal may include the target terminal, a serving cell for the target terminal, the interfering terminal, and the 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 position information. The configuration information of the interfering terminal may include location information and signal transmission power of the interfering terminal.

S704, determining a third interference value of the uplink signal of the interference terminal to the first downlink signal according to the interference elimination factor of the interference terminal, the signal transmission 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, and 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 an interfering terminal and a target terminal _1i ＝PL _ui -G _g -G _i 。PL _ui Representing a large scale path loss between the target terminal and the interfering terminal. G _i Representing the antenna gain of the interfering terminal.

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

B3＝∑ _{i belongs to the uplink} ηP _i /L _1i Formula six

Where B3 denotes a third interference value. η represents an interference cancellation factor. P _i Representing the signal transmission 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.

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

SINR is S1/(S1+ B1+ B2+ B3) formula seven

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

Based on the technical solution shown in fig. 7, an embodiment of the present application provides a method for detecting a downlink signal of a flexible frame structure simulation system, where when a serving cell sends a downlink signal to a terminal by using a flexible frame structure, the downlink signal received by the terminal from the serving cell may be interfered by a downlink signal and an 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 interference values of multiple interference sources (e.g., the downlink signal of the interfering cell, noise, the uplink signal of the interfering terminal, and the like) that generate interference on 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, establishing a channel matrix between a target terminal and a service cell and between the target terminal and a strong interference cell.

S801 may refer to the description of S701 and S702, which is not described herein again.

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

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

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

For S803, reference may be made to the description of S702 above, which is not repeated herein.

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

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.

S805, when the timeslot used by the interfering cell is an uplink timeslot, using a terminal of the interfering cell using the uplink timeslot as an interfering terminal.

The interfering terminal may also be referred to as a cross-slot interfering terminal.

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

For S806, reference may be made to the description of S703 above, which is not repeated herein.

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

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

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

It should be noted that, in this embodiment of the present application, when the simulation device starts to execute a simulation task, a large-scale path loss between the target terminal and the multiple interfering cells may be calculated first, and a strong interfering cell and a weak interfering cell in the multiple interfering cells may be determined according to the large-scale path loss between the target terminal and the multiple interfering cells. The simulation device may then establish a channel matrix with the strong interfering cell.

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.

S808 may refer to the technical solution of fig. 7, which is not described herein again.

It should be noted that, when the target terminal accesses a plurality of cells (including the serving cell and a plurality of interfering cells) in the simulation phase, the simulation apparatus may perform 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 a cell with a flexible frame structure, the simulation device may accurately and comprehensively determine the signal-to-noise ratio of the downlink signal received by the terminal by calculating interference values of interference cells (including a strong interference cell and a weak interference cell) and interference terminals (i.e., cross slot interference terminals) that generate interference on the downlink signal received by the 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.

All the schemes in the above embodiments of the present application can be combined without contradiction.

In the embodiment of the present application, the functional modules or functional units may be divided according to the method example, for example, each functional module or functional unit may be divided corresponding to each function, or two or more functions may be integrated into one processing module. The integrated module may be implemented in a form of hardware, or may be implemented in a form of a software functional module or a functional unit. The division of the modules or units in the embodiment of the present application is schematic, and is only a logic function division, and there may be another division manner in actual implementation.

In the case of dividing each functional module according to each function, fig. 9 shows a schematic structural diagram of a downlink signal detection apparatus 90, where the downlink signal detection apparatus 90 may be used to execute the functions related to the simulation device in the above-described embodiments. The downstream signal detecting device 90 shown in fig. 9 may include: a determining unit 901 and 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 the downlink signals of multiple interfering cells to the first downlink signal and a second interference value of the 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 the uplink signal of the interfering terminal to the first downlink signal according to the interference cancellation factor, the signal transmission power of the interfering terminal, and the link loss between the interfering terminal and the target terminal, where the uplink signal of the interfering terminal generates interference to the first downlink signal, and the interference cancellation factor of the interfering terminal is used to represent 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 multiple interfering cells include a strong interfering cell and a weak interfering cell, the strong interfering cell is an interfering cell whose large-scale path loss between the multiple interfering cells and the target terminal is greater than or equal to a preset threshold, and the weak interfering cell is an interfering cell whose large-scale path loss between the multiple interfering cells and the target terminal is less than the preset threshold, and the determining unit 901 is specifically configured to: calculating an interference value of a downlink signal of the strong interference cell to the first downlink signal according to the 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; calculating an interference value of a downlink signal of the weak interference cell to a first downlink signal according to the signal transmitting power of the weak interference cell and the link loss from the target terminal to the weak interference cell, wherein the first interference value comprises: the interference value of the downlink signal of the strong interference cell to the downlink signal of the serving cell and the interference value of the downlink signal of the weak interference cell to the downlink signal of the serving 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 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 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 interfering terminal, and determine a large-scale path loss between the target terminal and the interfering terminal; the processing unit 902 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.

In a possible implementation manner, as shown in fig. 9, the apparatus for detecting a downlink signal further includes a building unit 903, configured to build a channel matrix between a target terminal and a serving cell through simulation; the processing unit 902 is configured to determine, according to the signal transmission power of the serving cell, the channel matrix between the target terminal and the serving cell, and the precoding matrix of the serving cell, a signal when a downlink signal sent by the serving cell reaches the target terminal, 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 to obtain a first downlink signal.

In one possible implementation manner, the signal strength of the first downlink signal satisfies a first formula, where the first formula is: s1 ═ P | DHW- ² (ii) a Wherein S1 is the signal strength of the downlink signal, P is the signal transmission 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 is 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 a first interference value, B2 is a second interference value, and B3 is a third interference value.

As yet another implementable manner, the processing unit 902 in fig. 9 may be replaced by a processor, which may integrate the functions 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 embodiment of the present application may be the downlink signal detecting apparatus shown in fig. 3.

The embodiment of the application also provides a computer readable storage medium. All or part of the processes in the above method embodiments may be performed by relevant hardware instructed by a computer program, which may be stored in the above computer-readable storage medium, and when executed, may include the processes in the above method embodiments. The computer-readable storage medium may be an internal storage unit of the downlink signal detection apparatus (including the data sending end and/or the data receiving end) in any of the foregoing embodiments, for example, a hard disk or a memory of the downlink signal detection apparatus. The computer readable storage medium may also be an external storage device of the terminal device, such as a plug-in hard disk, a Smart Memory Card (SMC), a Secure Digital (SD) card, a flash memory card (flash card), and the like, which are provided on the terminal device. Further, the computer-readable storage medium may include both an internal storage unit and an external storage device of the downlink signal detection apparatus. The computer-readable storage medium stores the computer program and other programs and data necessary for 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 different objects and not for describing a particular order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively 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" means one or more, "a plurality" means two or more, "at least two" means two or three and three or more, "and/or" for describing an association relationship of associated objects, meaning that three relationships may exist, for example, "a and/or B" may mean: only A, only B and both A and B are present, wherein A and B may be singular or plural. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship. "at least one of the following" or similar expressions refer to any combination of these items, including any combination of the singular or plural items. 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.

Through the above description of the embodiments, it is clear to those skilled in the art that, for convenience and simplicity of description, the foregoing division of the functional modules is merely used as an example, and in practical applications, the above function distribution may be completed by different functional modules according to needs, that is, the internal structure of the device may be divided into different functional modules to complete all or part of the above described functions.

In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described device embodiments are merely illustrative, and for example, the division of the modules or units is only one logical functional division, and there may be other divisions when actually implemented, for example, a plurality of units or components may be combined or may be integrated into another device, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.

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

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 integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.

The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a readable storage medium. Based on such understanding, the technical solutions of the embodiments of the present application may be essentially or partially contributed to by the prior art, or all or part of the technical solutions may be embodied in the form of a software product, where the software product is stored in a storage medium and includes several instructions to enable a device (which may be a single chip, a chip, or the like) or a processor (processor) to execute all or part of the steps of the methods described in the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a U disk, a removable hard disk, a ROM, a RAM, a magnetic disk, or an optical disk.

The above description is only an embodiment of the present application, but the 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 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

1. A downlink signal detection method of a flexible frame structure simulation system, wherein the flexible frame structure simulation system includes a serving cell of a target terminal and a plurality of interfering cells, the method comprising:

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

determining a first interference value of downlink signals of the plurality of interfering cells to the first downlink signal and a second interference value of noise to the first downlink signal;

determining an interference elimination factor of an interference terminal according to a preset neural network algorithm, and 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 terminal, the signal transmission power of the interference terminal and the link loss between the interference terminal and the target terminal, wherein the interference terminal is a terminal which generates interference on the first downlink signal by the transmitted uplink signal, and the interference elimination 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;

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 include a strong interfering cell and a weak interfering cell, the strong interfering cell is an interfering cell with a large-scale path loss between the plurality of interfering cells and the target terminal being greater than or equal to a preset threshold, the weak interfering cell is an interfering cell with a large-scale path loss between the plurality of interfering cells and the target terminal being less than the preset threshold, and the determining a first interference value of downlink signals of the plurality of interfering cells on a downlink signal of the target terminal includes:

calculating an interference value of a downlink signal of the strong interference cell to the first downlink signal according to the 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;

calculating an interference value of a downlink signal of the weak interference cell to the first downlink signal according to the signal transmission power of the weak interference cell and the link loss from the target terminal to the weak interference cell, wherein the first interference value comprises: and the interference value of the downlink signal of the strong interference cell to the downlink signal of the serving cell and the interference value of the downlink signal of the weak interference cell to the downlink signal of the serving cell.

3. The method according to claim 1 or 2, wherein the determining the interference cancellation factor of the interfering terminal according to the predetermined neural network algorithm comprises:

acquiring 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, 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 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 elimination factor.

4. 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 value between the antenna gain of the target terminal and the antenna gain of the interference terminal.

5. The method of claim 1, further comprising:

establishing a channel matrix between the target terminal and the serving 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 performing linear detection on a signal when the downlink signal sent by the serving cell reaches the target terminal based on a preset detection algorithm to obtain the first downlink signal.

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

S1＝P|DHW| ² ；

wherein S1 is the signal strength of the first downlink signal, P is the signal transmission 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.

7. 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.

8. A downlink signal detection device of a flexible frame structure simulation system is characterized in that the flexible frame structure simulation system comprises a service 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 configured to determine the signal strength of the first downlink signal received by the target terminal;

the determining unit is further configured to determine a signal strength of a first downlink signal from the serving cell received by the target terminal;

the processing unit is configured to determine an interference cancellation factor of an 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 interfering terminal, signal transmission power of the interfering terminal, and link loss between the interfering terminal and the target terminal, where the interfering terminal is a terminal where a transmitted uplink signal interferes with the first downlink signal, and the interference cancellation factor of the interfering terminal is used to represent an interference degree of the uplink signal transmitted by the interfering terminal to the first downlink 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.

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

calculating an interference value of a downlink signal of the weak interference cell to the first downlink signal according to the signal transmission power of the weak interference cell and the link loss from the target terminal to the weak interference cell, where the first interference value includes: and the interference value of the downlink signal of the strong interference cell to the downlink signal of the serving cell and the interference value of the downlink signal of the weak interference cell to the downlink signal of the serving cell.

10. The apparatus according to claim 8 or 9, wherein the processing unit is specifically configured to:

11. The apparatus according to claim 8 or 9,

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

12. The apparatus according to claim 8, wherein the apparatus further comprises a setup unit:

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

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

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.

13. The apparatus of claim 12, wherein the signal strength of the first downlink signal satisfies a first formula, and wherein the first formula is:

S1＝P|DHW| ² ；

14. The apparatus of claim 8, wherein the signal-to-noise ratio satisfies a second formula, the second formula being:

SINR＝S1/(S1+B1+B2+B3)；

15. A computer-readable storage medium having stored therein instructions which, when executed, implement the method of any one of claims 1-7.

16. A signal detection device, comprising: a processor, a memory, and a communication interface; the communication interface is used for the signal detection device to communicate with other equipment or a network; the memory is used for storing one or more programs, the one or more programs comprising computer-executable instructions, which when executed by the signal detection apparatus, are executed by the processor to cause the signal detection apparatus to perform the method of any one of claims 1-7.