Time-varying channel estimation method and device, medium and product

Abstract

The invention discloses a time-varying channel estimation method and device, a medium and a product, and relates to the technical field of underwater acoustic communication, and the method comprises the steps: carrying out the preprocessing of a received signal, and obtaining a baseband signal; the method comprises the following steps of: performing channel initialization estimation by using a preamble according to a baseband signal; constructing a joint transmission matrix model by using the correlation between the channels at adjacent moments according to the initialized estimated values of the channels; detecting symbols at adjacent moments according to the joint transmission matrix model; taking the symbol with the minimum detection error in the symbols at the adjacent moments as a new pilot frequency; performing interference elimination on the new pilot frequency by using the detected symbols; and using the new pilot frequency after interference elimination to carry out iterative verification on the current time channel obtained based on the FBMC-OQAM channel estimation method until the error converges, outputting the current time channel, and carrying out channel estimation at the next time. According to the invention, the symbol detection accuracy during long data block transmission can be improved.

Description

Technical Field

[0001] The present application relates to the field of underwater acoustic communication technology, and in particular to a time-varying channel estimation method, device, medium and product. Background Art

[0002] With the rapid development of underwater acoustic communication technology, communication systems based on underwater acoustic filter bank multi-carrier-offset quadrature amplitude modulation (FBMC-OQAM) are gradually being used in underwater acoustic channel environments due to their anti-interference capabilities under Doppler frequency offset. Although the traditional orthogonal frequency division multiplexing (OFDM) system has been widely used, its performance in time-varying channels is poor, especially in the transmission of long data blocks, which will encounter serious inter-symbol interference and inter-carrier interference. In contrast, the FBMC-OQAM system limits the out-of-band energy leakage by windowing each subcarrier, significantly reducing the system's sensitivity in the presence of frequency offset.

[0003] In the actual underwater acoustic channel environment, due to the channel fading caused by time-frequency dual selectivity, the time-varying characteristics of the channel make it difficult for the channel estimation method based on the time-invariant assumption to guarantee the demodulation accuracy of the signal. The traditional FBMC-OQAM channel estimation method usually performs channel estimation based on the initial pilot signal. During the transmission of long data blocks, the channel will change significantly, which makes the initial channel estimation result unable to adapt to the detection of subsequent symbols.

[0004] In order to cope with the impact of time-varying channels on signal transmission performance, it is urgent to provide a new time-varying channel estimation method. Summary of the invention

[0005] The purpose of this application is to provide a time-varying channel estimation method, device, medium and product, which can solve the problem of insufficient accuracy of time-varying channel estimation in the prior art and improve the accuracy of symbol detection during long data block transmission.

[0006] To achieve the above objectives, this application provides the following solutions:

[0007] In a first aspect, the present application provides a time-varying channel estimation method, wherein the time-varying channel estimation method is based on an FBMC-OQAM communication system; the time-varying channel estimation method comprises:

[0008] Preprocessing the received signal to obtain a baseband signal; the preprocessing includes: performing baseband sampling, frequency offset compensation and multi-carrier demodulation in an FBMC-OQAM demodulator;

[0009] According to the baseband signal, the channel initialization estimation is performed using the preamble code to obtain the initialization estimation value of the channel;

[0010] According to the initial estimation value of the channel, the correlation between channels at adjacent moments is used to construct a joint transmission matrix model;

[0011] Detecting adjacent time symbols according to a joint transmission matrix model;

[0012] The symbol with the smallest detection error among the adjacent time symbols is used as a new pilot;

[0013] Using the detected symbols to perform interference elimination on the new pilot;

[0014] The new pilot after interference elimination is used to iteratively check the current channel obtained based on the FBMC-OQAM channel estimation method until the error converges, then the current channel is output and the next channel estimation is performed.

[0015] Optionally, the preprocessing the received signal to obtain a baseband signal specifically includes:

[0016] The received signal y(t) is converted into a baseband discrete received sequence y(l) by using down-mixing, root raised cosine matched filtering and down-sampling baseband sampling processing;

[0017] Using the formula Perform multi-carrier demodulation on the baseband discrete received sequence y(l) to obtain the baseband symbol z at each subcarrier and each time m′,n′ ;

[0018] Among them, φ m′,n′ is the phase rotation of the (m', n')th symbol, φ m′,n′ =π(m′+n′) / 2+m′n′π, L is the length of the prototype filter, l is the discrete sampling time sequence number, the received signal y(l) is represented by the convolution of the transmitted signal and the channel impulse response, M is the symbol period of the FBMC-OQAM communication system, g(·) represents the prototype filter, m′ is the m′th subcarrier, n′ is the n′th symbol time, π is pi, j is the imaginary unit, and e is the Euler number.

[0019] Optionally, performing channel initialization estimation using a preamble according to the baseband signal to obtain an initialization estimation value of the channel specifically includes:

[0020] FBMC-OQAM channel estimation method based on weighted least squares.

[0021] Optionally, according to the initialization estimation value of the channel, the correlation between channels at adjacent moments is used to construct a joint transmission matrix model, which specifically includes the following formula:

[0022]

[0023] in, is the transmission matrix, k is the kth tap, and parameter φ Δ =φ m,n -φ m′,n′ ,φ m,n is the phase rotation of the (m, n)th symbol, φ m,n =π(m+n) / 2+mnπ,h n′ (k) is the kth tap in the channel time domain impulse response at the n′th symbol time.

[0024] Optionally, using the detected symbols to perform interference elimination on the new pilot signal specifically includes:

[0025] When n'=4, using the formula Get the new pilot after interference elimination

[0026] in, is the detection symbol at time n′=4, z m′,4 is the symbol when n′=4, parameter Ω={(m,n)|m∈{m′-1,m′,m′+1},n∈{n′-4,…,n′+4},and,(m,n)neq(m′,n′)}, is the contribution of the (m, n)th symbol to the (m', n')th symbol after passing through the channel.

[0027] Optionally, the iterative verification of the current moment channel obtained based on the FBMC-OQAM channel estimation method using the new pilot after interference elimination until the error converges, then outputting the current moment channel, and performing channel estimation at the next moment, specifically includes:

[0028] A channel with the strongest energy in the middle of a symbol in a FBMC-OQAM communication system is selected to estimate the channel at the next moment.

[0029] In a second aspect, the present application provides a time-varying channel estimation device, the time-varying channel estimation device comprising:

[0030] The FBMC-OQAM demodulator is used to pre-process the received signal to obtain a baseband signal; the pre-processing includes: performing baseband sampling, frequency offset compensation and multi-carrier demodulation in the FBMC-OQAM demodulator;

[0031] The channel initialization estimation module is used to perform channel initialization estimation based on the baseband signal using the preamble code to obtain an initialization estimation value of the channel;

[0032] A joint transmission matrix model building module is used to build a joint transmission matrix model based on the initialization estimation value of the channel and the correlation between channels at adjacent moments;

[0033] A symbol detection module, used to detect adjacent time symbols according to a joint transmission matrix model;

[0034] A new pilot selection module is used to select a symbol with the smallest detection error among adjacent time symbols as a new pilot;

[0035] A new pilot interference elimination module is used to eliminate interference of the new pilot using the detected symbols;

[0036] The time-varying channel estimator is used to iteratively check the current moment channel obtained based on the FBMC-OQAM channel estimation method using the new pilot after interference elimination until the error converges, then output the current moment channel and perform channel estimation at the next moment.

[0037] In a third aspect, the present application provides a computer device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the time-varying channel estimation method.

[0038] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which implements the time-varying channel estimation method when executed by a processor.

[0039] In a fifth aspect, the present application provides a computer program product, including a computer program, which implements the time-varying channel estimation method when executed by a processor.

[0040] According to the specific embodiments provided in this application, this application has the following technical effects:

[0041] The present application provides a time-varying channel estimation method, device, medium and product, which performs channel tracking estimation by reusing the channel estimation result of the previous moment and combining the correlation between channels at adjacent moments. The present application can effectively improve the accuracy of channel estimation, and can significantly reduce the bit error rate and improve the accuracy of symbol detection during the transmission of long data blocks. The present application can further improve the accuracy of channel tracking and effectively avoid the impact of rapid channel changes on signal detection during the transmission of long data blocks; and can significantly reduce the bit error rate and improve the communication performance of the system in complex underwater acoustic environments; and further has better adaptability and stability in complex marine environments. Compared with traditional methods based on scattered pilots, the present application has less overhead, which is conducive to improving the spectrum efficiency of the communication system. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0043] Figure 1 This is a schematic diagram of a flow chart of a time-varying channel estimation method in one embodiment of the present application;

[0044] Figure 2 This is a flowchart of a time-varying channel estimation method in an embodiment of the present application;

[0045] Figure 3 The structure diagram of the data packet to be sent;

[0046] Figure 4 It is the time coherence diagram of the simulation channel;

[0047] Figure 5 Schematic diagram of symbol detection results of FBMC-OQAM communication system under time-varying channel. DETAILED DESCRIPTION

[0048] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0049] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0050] In an exemplary embodiment, Figure 1 and Figure 2 As shown, a time-varying channel estimation method is provided, and the time-varying channel estimation method is based on the FBMC-OQAM communication system, and the method includes the following S101 to S107. Wherein:

[0051] S101, preprocessing the received signal to obtain a baseband signal; the preprocessing includes: baseband sampling, frequency offset compensation and multi-carrier demodulation in the FBMC-OQAM demodulator; frequency offset compensation is to estimate the Doppler frequency offset and residual carrier frequency offset commonly seen in underwater acoustic signals, and compensate for the estimated average Doppler frequency offset by resampling, and compensate for the residual carrier frequency offset (CFO) by multiplying the frequency offset coefficient.

[0052] S102 specifically includes:

[0053] The received signal y(t) is converted into a baseband discrete received sequence y(l) by using down-mixing, root raised cosine matched filtering and down-sampling baseband sampling processing;

[0054] Using the formula Perform multi-carrier demodulation on the baseband discrete received sequence y(l) to obtain the baseband symbol z at each subcarrier and each time m′,n′ ;

[0055] Among them, φ m′,n′ is the phase rotation of the (m', n')th symbol, φ m′,n′ =π(m′+n′) / 2+m′n′π, L is the length of the prototype filter, l is the discrete sampling time sequence number, the received signal y(l) is represented by the convolution of the transmitted signal and the channel impulse response, M is the symbol period of the FBMC-OQAM communication system, g(·) represents the prototype filter, m′ is the m′th subcarrier, n′ is the n′th symbol time, π is the circumference, j is the imaginary unit, and e is the Euler number. In the example, the time period of the prototype filter is 4 times the symbol period of the FBMC-OQAM communication system, that is, L=KM=4M, K represents the prototype filter expansion coefficient, K=4.

[0056] S102, based on the baseband signal, the channel is initialized and estimated using the preamble code to obtain an initialization estimation value of the channel; the initialization estimation value of the channel is the channel at the start time of the FBMC-OQAM signal block (n′=0 time), that is, Among them, the kth tap is

[0057] The FBMC-OQAM channel estimation method is performed based on weighted least squares (weightedLS, WLS).

[0058] like Figure 3 The transmission data packet structure in , preamble is used for CFO estimation and channel estimation. T is the time interval between adjacent FBMC-OQAM symbols. The preamble is composed of known pilot symbols and empty subcarriers arranged alternately in the frequency dimension to avoid interference between pilot symbols. The data symbol and the preamble are protected by the time interval of N = 3 empty symbols. It can be considered that the pilot symbols in the preamble are not interfered by the unknown data symbols behind.

[0059] Therefore, for a FBMC-OQAM communication system that compensates for over-frequency offset well, the received symbol z p,q It can be expressed as:

[0060]

[0061] Where g(·) represents the prototype filter, p is the p-th subcarrier in an FBMC multicarrier symbol, q is the q-th FBMC multicarrier symbol in the time dimension of the data block, the value range of p is [-M / 2, M / 2-1], and the value range of q is [0, N-1]. After expansion, we can get:

[0062]

[0063] Where m is the mth subcarrier in an FBMC multicarrier symbol, n is the nth FBMC multicarrier symbol in the time dimension of the data block, the value range of m is [-M / 2, M / 2-1], and the value range of n is [0, N-1]. Since the interference of data symbols can be ignored, the preamble symbol can be expressed as:

[0064]

[0065] Convert the above formula into matrix form:

[0066] z0=Λh+η0;

[0067] Among them, the received pilot symbol vector z0, the time domain channel impulse response (CIR) vector h to be estimated, the noise vector η0 and the transmission matrix Λ are expressed as:

[0068]

[0069] The superscript T indicates transposition, and the subvector Indicates N pilot symbols on subcarriers, Indicates The Nth noise sub-carrier on each 1×N k λ-dimensional column vector m Defined as:

[0070]

[0071] Estimation of CIR The weighted least squares method can be used to obtain:

[0072]

[0073] in, is the covariance matrix of noise η0, and the superscript H represents the conjugate transpose.

[0074] S103, constructing a joint transmission matrix model based on the initialization estimation value of the channel and utilizing the correlation between channels at adjacent moments;

[0075] according to Figure 2 As shown, at the beginning, the channel estimation values ​​at time n′=0 and time n′={1,2,…,N} are input respectively;

[0076] When this step is first performed, the only known channels are And no When input again after subsequent steps, the number of known channels is increased, and the new estimated Update n′ (k), as the number of iterations increases, ...and other gradual updates, such as Figure 3 As shown, the guard interval after the preamble lasts for 3 symbol periods, that is, the symbol at n′=1, 2 and 3 is 0, and the channel cannot and does not need to be estimated. Therefore, the second estimated channel time domain pulse response is

[0077] Combine the estimated channels and replace the unknown channels with the channels at adjacent times, and put them into the formula middle;

[0078] The superscript tv indicates “time-varying”. is the transmission matrix, k is the kth tap, and parameter φ Δ =φ m,n -φ m′,n′ ,φ m,n is the phase rotation of the (m, n)th symbol, φ m,n =π(m+n) / 2+mnπ,h n′(k) is the kth tap in the channel time domain impulse response at the n′th symbol time. S104, detect the adjacent symbol time according to the joint transmission matrix model.

[0079] Specifically, when only known When the estimated detection symbol In the above example, only the data symbols at the first few moments can be estimated accurately, but as the known channel is continuously updated, the detected symbols The estimates will become more and more accurate.

[0080] S105, using the symbol with the smallest detection error among the adjacent time symbols as a new pilot;

[0081] Specifically, the estimation of the channel requires the assistance of known pilots. To estimate the channel at time n′, the transmission and reception pilots at time n′ can be obtained. The pilot at time n′ is obtained based on the channel detection of n′-1 and before, and there is a detection error. Therefore, the symbol whose detection value is close to the fixed constellation point is selected as the new pilot, which can reduce the error. The estimation error.

[0082] The number of channel pilot selections is determined based on the channel estimation method and the channel freedom. Assume that the subscript m′ of the selected new pilots constitutes the set From the received symbol z m′,n′ Select the symbol with the same subscript as the new receiving pilot

[0083] S106, using the detected symbols to eliminate interference with the new pilot;

[0084] When n'=4, using the formula Get the new pilot after interference elimination

[0085] in, is the detection symbol at time n′=4, z m′,4 is the symbol when n′=4, parameter Ω={(m,n)|m∈{m′-1,m′,m′+1},n∈{n′-4,...,n′+4},and,(m,n)neq(m′,n′)}, is the contribution of the (m, n)th symbol to the (m', n')th symbol after passing through the channel.

[0086] S107, using the new pilot after interference elimination, iteratively verify the current moment channel obtained based on the FBMC-OQAM channel estimation method until the error converges, then output the current moment channel, and perform next moment channel estimation.

[0087] S107 specifically includes:

[0088] Select a channel with the strongest energy in the middle of a symbol in the FBMC-OQAM communication system to estimate the channel at the next moment. The channel with the strongest energy in the middle of a symbol takes the value of the time sampling number l as M / 2n′+2M;

[0089] Specifically, the temporal coherence function Θ(τ) is defined as:

[0090]

[0091] The angle brackets represent the maximum value after the two time series are correlated. E[·] represents the expectation, that is, the average value in the time dimension. * (t) is the conjugate of the received signal, h(t) is the received signal and τ is the time delay.

[0092] The simulation is performed through a specific embodiment. In this embodiment, an underwater acoustic channel simulation model is used, and the simulation modulation parameters of FBMC-OQAM are set to M=128, N=29. Then the discrete sequence length of an FBMC-OQAM signal block is MN / 2+3.5M=2304. When the signal bandwidth is 3000Hz, the corresponding transmission time of the signal block is 768ms. The channel geometry parameters in the channel parameters are set to a water depth of 80m, a sound source depth of 20m, a receiving depth of 30m, a transmitting and receiving distance of 1000m, an expansion coefficient of 1.8, a bandwidth of 3000Hz, an amplitude ratio of the strongest path to the weakest path of 10, a sound speed of 1540m / s in water, and a sound speed of 1580m / s in the seabed sediment layer; the small-scale parameters are set to a coherence time of 10s, a micro-multipath number of 20, an average amplitude of the micro-multipath of 0.0707, and a variance of the micro-multipath amplitude of 10. -6 ; The large-scale parameter settings include the water surface wave height variation range of -0.5~0.5m, the sound source height variation range of -0.2~0.2m, the receiver height variation range of -0.1~0.1m, and the transmission and reception spacing variation range of -2~2m.

[0093] Figure 4 The temporal coherence function of the generated channel is calculated, that is, the correlation coefficients of the channels at each time are compared with the channel at time 0. The coherence coefficients between channels at different times constitute the temporal coherence function of the time-varying channel, and its physical meaning is the similarity between the channel impulse responses at different times. Figure 4 The figure also shows the actual waveform of a FBMC-OQAM long signal block with parameters M=128 and N=29. Within one FBMC-OQAM signal block period (0.768s), the channel correlation coefficient drops from 1 to about 0.823.

[0094] If you only use The symbol detection is performed on the entire signal block, and the detection result is as follows: Figure 5 As shown in part (a) of . As n increases, the channel difference at different times increases, resulting in a decrease in symbol detection accuracy. When the present application is used for channel tracking, the tracked time-varying channel is incorporated into the UTM model, which can improve the symbol detection result, such as Figure 5 As shown in part (b) of . Figure 5 The scattered points in part (b) of do not diverge with the increase of n. The results show that the present application can reduce the bit error rate of the long signal block FBMC-OQAM communication system.

[0095] Based on the same inventive concept, the embodiment of the present application also provides a time-varying channel estimation device for implementing the time-varying channel estimation method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more time-varying channel estimation device embodiments provided below can refer to the limitations of the time-varying channel estimation method above, and will not be repeated here.

[0096] In an exemplary embodiment, a time-varying channel estimation device is provided, comprising:

[0097] The FBMC-OQAM demodulator is used to pre-process the received signal to obtain a baseband signal; the pre-processing includes: performing baseband sampling, frequency offset compensation and multi-carrier demodulation in the FBMC-OQAM demodulator;

[0098] The channel initialization estimation module is used to perform channel initialization estimation based on the baseband signal using the preamble code to obtain an initialization estimation value of the channel;

[0099] A joint transmission matrix model building module is used to build a joint transmission matrix model based on the initialization estimation value of the channel and the correlation between channels at adjacent moments;

[0100] A symbol detection module, used to detect adjacent time symbols according to a joint transmission matrix model;

[0101] A new pilot selection module is used to select a symbol with the smallest detection error among adjacent time symbols as a new pilot;

[0102] A new pilot interference elimination module is used to eliminate interference of the new pilot using the detected symbols;

[0103] The time-varying channel estimator is used to iteratively check the current moment channel obtained based on the FBMC-OQAM channel estimation method using the new pilot after interference elimination until the error converges, then output the current moment channel and perform channel estimation at the next moment.

[0104] In an exemplary embodiment, a computer device is provided, which may be a server or a terminal. The computer device includes a processor, a memory, an input / output interface (I / O for short) and a communication interface. The processor, the memory and the input / output interface are connected via a system bus, and the communication interface is connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, a time-varying channel estimation method is implemented.

[0105] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0106] In an exemplary embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0107] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0108] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0109] The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. The non-relational database may include a distributed database based on blockchain, etc., but is not limited thereto. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but is not limited thereto.

[0110] In this application, all actions to obtain signals, information or data are carried out in compliance with the relevant data protection laws and policies of the country where they are located and with the authorization given by the owner of the corresponding device.

[0111] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0112] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A time-varying channel estimation method, characterized in that: The time-varying channel estimation method is based on the FBMC-OQAM communication system; The time-varying channel estimation method comprises: Preprocessing the received signal to obtain a baseband signal; the preprocessing includes: performing baseband sampling, frequency offset compensation and multi-carrier demodulation in an FBMC-OQAM demodulator; According to the baseband signal, the channel initialization estimation is performed using the preamble code to obtain the initialization estimation value of the channel; According to the initial estimation value of the channel, the correlation between channels at adjacent moments is used to construct a joint transmission matrix model; Detecting adjacent time symbols according to a joint transmission matrix model; The symbol with the smallest detection error among the adjacent time symbols is used as a new pilot; Using the detected symbols to perform interference elimination on the new pilot; The new pilot after interference elimination is used to iteratively check the current channel obtained based on the FBMC-OQAM channel estimation method until the error converges, then the current channel is output and the next channel estimation is performed.

2. The time-varying channel estimation method according to claim 1, characterized in that: The preprocessing of the received signal to obtain a baseband signal specifically includes: The received signal y(t) is converted into a baseband discrete received sequence y(l) by using down-mixing, root raised cosine matched filtering and down-sampling baseband sampling processing; Using the formula Perform multi-carrier demodulation on the baseband discrete received sequence y(l) to obtain the baseband symbol z at each subcarrier and each time m′,n′ ; Among them, φ m′,n′ is the phase rotation of the (m', n')th symbol, φ m′,n′ =π(m′+n′) / 2+m′n′π, L is the length of the prototype filter, l is the discrete sampling time sequence number, the received signal y(l) is represented by the convolution of the transmitted signal and the channel impulse response, M is the symbol period of the FBMC-OQAM communication system, g(·) represents the prototype filter, m′ is the m′th subcarrier, n′ is the n′th symbol time, π is pi, j is the imaginary unit, and e is the Euler number.

3. The time-varying channel estimation method according to claim 1, characterized in that: The method of performing channel initialization estimation using a preamble code according to a baseband signal to obtain an initialization estimation value of the channel specifically includes: FBMC-OQAM channel estimation method based on weighted least squares.

4. The time-varying channel estimation method according to claim 2, characterized in that: According to the initial estimation value of the channel, the correlation between channels at adjacent times is used to construct a joint transmission matrix model, which specifically includes the following formula: in, is the transmission matrix, k is the kth tap, and parameter φ Δ =φ m,n -φ m′,n′ ,φ m,n is the phase rotation of the (m, n)th symbol, φ m,n =π(m+n) / 2+mnπ,h n′ (k) is the kth tap in the channel time domain impulse response at the n′th symbol time.

5. The time-varying channel estimation method according to claim 4, characterized in that: The detected symbols are used to eliminate interference from the new pilot, specifically including: When n'=4, using the formula Get the new pilot after interference elimination in, is the detection symbol at time n′=4, z m′,4 is the symbol when n′=4, parameter Ω={(m,n)|m∈{m′-1,m′,m′+1},n∈{n′-4,…,n′+4},and,(m,n)neq(m′,n′)}, is the contribution of the (m, n)th symbol to the (m', n')th symbol after passing through the channel.

6. The time-varying channel estimation method according to claim 1, characterized in that: The new pilot after interference elimination is used to iteratively check the current moment channel obtained based on the FBMC-OQAM channel estimation method until the error converges, then the current moment channel is output, and the next moment channel estimation is performed, specifically including: A channel with the strongest energy in the middle of a symbol in a FBMC-OQAM communication system is selected to estimate the channel at the next moment.

7. A time-varying channel estimation device, characterized in that: The time-varying channel estimation device comprises: The FBMC-OQAM demodulator is used to pre-process the received signal to obtain a baseband signal; the pre-processing includes: performing baseband sampling, frequency offset compensation and multi-carrier demodulation in the FBMC-OQAM demodulator; The channel initialization estimation module is used to perform channel initialization estimation based on the baseband signal using the preamble code to obtain an initialization estimation value of the channel; A joint transmission matrix model building module is used to build a joint transmission matrix model based on the initialization estimation value of the channel and the correlation between channels at adjacent moments; A symbol detection module, used to detect adjacent time symbols according to a joint transmission matrix model; A new pilot selection module is used to select a symbol with the smallest detection error among adjacent time symbols as a new pilot; A new pilot interference elimination module is used to eliminate interference of the new pilot using the detected symbols; The time-varying channel estimator is used to iteratively check the current moment channel obtained based on the FBMC-OQAM channel estimation method using the new pilot after interference elimination until the error converges, then output the current moment channel and perform channel estimation at the next moment.

8. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the time-varying channel estimation method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the time-varying channel estimation method according to any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the time-varying channel estimation method according to any one of claims 1 to 6 is implemented.

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