Orthogonal time-frequency-space modulation based perception-aided uplink channel estimation method and system

Abstract

The application provides a sensing-assisted uplink channel estimation method and system based on orthogonal time-frequency-space modulation, comprising: generating pilot symbols in the time-delay Doppler domain, superimposing the pilot symbols with communication data symbols to form a transmission frame; converting the time-delay Doppler domain transmission frame into a time-domain uplink signal, and re-converting the time-domain uplink signal into a time-delay Doppler domain receiving signal at a receiving end base station; causing the base station to collect a sensing echo, and the backscattering signal formed by the most recently transmitted downlink signal being emitted or diffracted by a user and a potential target object; estimating the time-delay and Doppler parameters at the receiving end by using the uplink pilot and the sensing echo; and eliminating the interference of the communication data and the pilot symbols to each other at the receiving end by using the estimated time-delay and Doppler parameters, and simultaneously performing channel estimation and data detection. The method and system provided by the application have low complexity and are easy to implement; meanwhile, the channel estimation and data detection are more accurate, and the communication sensing capability of the orthogonal time-frequency-space waveform in a high-mobility scenario can be effectively utilized.

Description

Technical Field

[0001] This invention relates to the field of wireless communication and integrated communication sensing technology, specifically to a sensing-assisted uplink channel estimation method and system based on orthogonal time-frequency regulation. Background Technology

[0002] Orthogonal Frequency Division Multiplexing (OFDM) is widely used in fourth-generation and fifth-generation mobile communication systems due to its advantages such as high spectral efficiency and strong resistance to multipath effects. Its main idea is to divide a wideband channel into several orthogonal sub-channels, converting the high-speed data stream into parallel low-speed sub-data streams and modulating them onto each sub-channel for transmission. The frequency spacing between subcarriers avoids mutual interference, and the bandwidth of each sub-channel is smaller than the coherence bandwidth, causing the signal to experience flat fading rather than frequency-selective fading during transmission.

[0003] However, in future sixth-generation mobile communication systems, the significant Doppler frequency shift caused by high frequencies and high mobility often leads to severe inter-carrier interference in OFDM waveforms. To address this issue, Orthogonal Time-Frequency Space Modulation (OTFS) was proposed in the paper "Orthogonal Time-Frequency Space Modulation" and has been proven to not only overcome frequency-selective fading caused by multipath effects like OFDM, but also combat time-selective fading caused by relative motion. The core idea of ​​OTFS is to transmit information in the delay-Doppler domain rather than the time-frequency domain. The delay-Doppler domain channel can be considered a "snapshot" of the real wireless environment; only sudden changes in propagation path length and movement speed will cause changes in channel parameters. Therefore, the channel characteristics in the delay-Doppler domain are much slower than those in the time-frequency domain. Furthermore, the wireless propagation environment generally contains only a limited number of moving scatterers or reflectors, which manifests as a sparse channel response in the delay-Doppler domain.

[0004] Most existing OTFS channel estimation methods are proposed under the condition of considering only integer Doppler. The paper "Data-aided channel estimation for OTFS systems with a superimposed pilot and data transmission scheme" proposes a scheme to complete time-delay-Doppler domain channel estimation using a single superimposed pilot. The pilot symbol power needs to be high enough, otherwise it will be "submerged" in data and noise and cannot be detected at the receiver. The paper "OTFS channel estimation and data detection designs with superimposed pilots" proposes a scheme to superimpose all pilot symbols in the time-delay-Doppler domain. This eliminates the need to allocate high power to the pilot, but the interference between data and pilot is stronger, requiring prior knowledge of time-delay-Doppler parameters and complex interference cancellation algorithms to ensure channel estimation accuracy. Considering only the integer Doppler case simplifies the design of the delay-Doppler domain channel estimation system and the processing algorithm at the receiver. However, in real-world scenarios and devices, to meet the requirements of low-latency communication, the symbol duration and the number of transmission slots cannot be too high. This results in insufficient Doppler resolution, causing the Doppler spread of the channel to fall between adjacent Doppler grid points instead of being "captured" by Doppler grid points with integer multiple resolution. If the assumption of integer Doppler is still used to estimate the channel, it will cause significant estimation errors, leading to a serious deterioration in communication effectiveness.

[0005] In contrast to the integer Doppler case is the fractional Doppler case. The paper "Embedded pilot-aided channel estimation for otfs in delay-doppler channels" uses a single embedded pilot symbol with a blank guard interval to estimate the delay-Doppler parameters and channel gain. While this scheme is applicable to both integer and fractional Doppler cases, the latter requires a larger guard interval, significantly reducing spectral efficiency. Furthermore, because multiple integer Dopplers are used to approximate fractional Doppler, the channel estimation is not accurate enough. The paper "Integrated sensing and communication-assisted orthogonal time-frequency spacetransmission for vehicular networks" proposes using a sensing system to estimate delay and Doppler parameters, thereby simplifying the design of communication pilots and achieving a certain degree of communication-sensing fusion. However, it is still based on the integer Doppler assumption and does not fully explore the auxiliary potential of sensing for communication. Summary of the Invention

[0006] To address the shortcomings of existing technologies, the purpose of this invention is to provide a sensing-assisted uplink channel estimation method and system based on orthogonal time-frequency regulation.

[0007] A sensing-assisted uplink channel estimation method based on orthogonal time-frequency regulation, provided by the present invention, includes:

[0008] Step S1: Generate pilot symbols in the time-delay Doppler domain and superimpose them with communication data symbols to form a transmission frame;

[0009] Step S2: Convert the time-delay Doppler domain transmission frame into a time-domain uplink signal, transmit it through the transmitting end user, and after passing through the wireless channel, convert it back into a time-delay Doppler domain reception signal at the receiving end base station;

[0010] Step S3: Instruct the base station to collect sensing echoes and convert the backscattered signals formed by the transmission or diffraction of the recently transmitted downlink signals by users and potential targets into the time-delay Doppler domain;

[0011] Step S4: At the receiving end, time delay and Doppler parameters are estimated using uplink pilot and sensing echo;

[0012] Step S5: Using the estimated time delay and Doppler parameters, eliminate the interference between communication data and pilot symbols at the receiving end, and simultaneously perform channel estimation and data detection.

[0013] Preferably, in step S1:

[0014] Measure the maximum delay spread and maximum Doppler spread of the channel, and determine the relationship between channel spread and delay-Doppler domain index:

[0015]

[0016] Where, τ i , which represents the delay spread of a certain path, v i For Doppler extension, i is the index of the path, l i k is the delay axis index corresponding to the delay spread. j The Doppler axis index corresponds to the Doppler extension; M is the number of time delay blocks in the time-delay Doppler domain planar grid, N is the number of Doppler blocks in the time-delay Doppler domain planar grid, Δf is the subcarrier frequency interval, and T is the symbol duration; the maximum time delay index l in the time-delay Doppler domain is calculated. max The maximum Doppler index is k max Randomly generate a total of N p =(2l) max +1)(4k max +1) pilot symbol;

[0017] The selected range is k∈[k p -k max k p +k max ], l∈[l p , l p +l max ], where k p ∈[0, N-1], l p ∈[0, M-1], k max For the Doppler axis index corresponding to the maximum Doppler extension, l max The delay axis index corresponding to the maximum delay extension;

[0018] The pilot symbols are superimposed one by one onto the time-delayed Doppler domain data symbols X within this range. DD superior:

[0019] X DD =X d +X p

[0020] Where X d X is a matrix-form communication data symbol. p The pilot symbols are in matrix form.

[0021] Preferably, in step S2:

[0022] The time-delay Doppler domain symbols are converted into time-frequency domain signals by inverse discrete symmetric Fourier transform:

[0023]

[0024] Where, x TF [m, n] represents the time-frequency domain transmitted signal, and x[k, l] is the time-delay Doppler domain symbol X. DD The elements are m = 0, 1...M-1; n = 0, 1...N-1; e is the base of the natural logarithm, and j is the imaginary unit;

[0025] The time-frequency domain symbol is transformed into a baseband time-domain signal s(t) using the Heisenberg transform:

[0026]

[0027] Where gtx(t) represents the transmitted pulse waveform, which uses rectangular transmitted and received waveforms, and inserts a cyclic prefix in the time domain to form the final transmitted signal; t indicates that the independent variable of the function is time;

[0028] s(t) can be expressed in matrix form:

[0029]

[0030] Where H is the conjugate transpose operation of the matrix; X DD Transmit signals in matrix form for the time-delay-Doppler domain; and To obtain the normalized DFT matrix, vectorize S to get s:

[0031]

[0032] in, vec() is a column vectorization operation. It is the Kronecker product, where C represents the complex number, and I... M It is an identity matrix of size M×M;

[0033] Since the channel exhibits sparsity in the time-delay Doppler domain, the complex baseband channel impulse response h(τ, v) is expressed as:

[0034]

[0035] Where P represents the number of multipath components, which is also the number of channel taps in the time-delay Doppler domain, and h i τ represents the complex channel gain of the i-th path; i Let v represent the delay of the i-th path. i Let δ represent the Doppler frequency shift of the i-th path; δ is the impulse function, τ is the time delay, and v is the Doppler frequency shift.

[0036] Delay Doppler domain channel taps and τ i vi The relationship is:

[0037]

[0038] Among them, l i With k i Let these represent the indices of the integer delay tap and the Doppler tap corresponding to the i-th path, respectively, and the fractional Doppler κ. i This represents the offset from the nearest integer tap, whose size satisfies -0.5 < κ. i ≤0.5, and the relationship between the maximum channel delay spread and maximum Doppler spread and the delay-Doppler domain index is obtained as follows:

[0039]

[0040] Where, τ max For the maximum delay spread of the channel, v max For maximum Doppler extension, l max k is the delay axis index in the Doppler domain corresponding to the maximum delay spread. max The time-delay Doppler domain Doppler axis index corresponding to the maximum Doppler extension;

[0041] The signal s(t) is transmitted in the time-varying channel described above, and the received signal r(t) is given by the following equation:

[0042] r(t)=∫∫h(τ,v)s(t-τ)e j2πv(t-τ) dτdv+w(t)

[0043] Where w(t) is zero-mean additive white Gaussian noise, and its variance is...

[0044] Represent r(t) in vector form as r:

[0045] r = Hs + w

[0046] in, Let Δ be the forward cyclic shift matrix used to characterize the delay, and let Δ be a diagonal matrix. Used to characterize Doppler frequency shift

[0047] At the receiving end, the cyclic prefix is ​​first removed in the time domain, and then the signal is transformed to the time-frequency domain and the time-delay Doppler domain successively through Wigner transform and discrete symmetric Fourier transform. The above process can be represented by a matrix as follows:

[0048]

[0049] Among them, Y TF and Y DDThese are the matrix forms of the received signals in the time-frequency domain and the time-delay Doppler domain, respectively, where R is the received signal matrix in the time-delay domain; for Y... DD Vectorization yields:

[0050]

[0051] in, Denotes the time-delay Doppler domain equivalent channel matrix.

[0052] Step S3 includes:

[0053] The same operation as in step S2 is performed on the sensing echo generated by the downlink signal, converting it to the time-delay Doppler domain to obtain y. s .

[0054] Preferably, in step S4:

[0055] Step S4.1: At the receiving end, extract some sampling points from the received signal in the time-delay Doppler domain, construct the sensing matrix and the vector to be reconstructed based on the known uplink pilot, and estimate the integer time-delay Doppler parameters;

[0056] Step S4.2: Utilize the sensing echo y formed by the downlink signal s The fractional Doppler estimate is obtained by iteratively searching within the neighborhood of the integer Doppler parameters.

[0057] Preferably, step S4.1 includes:

[0058] For the received signal Y DD Extract sampling points within a given range, i.e., k∈[k p -k max k p +k max ], l∈[l p , l p +l max ], forming the measurement vector y p ;

[0059] According to the pilot matrix X p Constructing a matrix Each column ψ k′，l′ =vec(X′) p ), X′ p element x′ p [k, l] = x p ([kk′) N ,[ll′] M ), [] N and[] MThese are cyclic shift operations modulo N and M, respectively, where the elements of the pilot matrix are:

[0060]

[0061] in, The power of the pilot symbol;

[0062] Get the initial Then, similarly according to the range k∈[k p -k max k p +k max ], l∈[l p , l p +l max Extract The corresponding row, which is an M×N 0-1 matrix and its column vectorization, then the row index of 1 is the row to be extracted. The row index, after being updated, results in a smaller value.

[0063] Construct the perception matrix A:

[0064]

[0065] Where Φ is the phase offset matrix, and ⊙ represents the Hadamard product;

[0066] Searching for the column in A that best matches the current residual yields an integer time-delay Doppler index for a path, namely:

[0067]

[0068] Where ψ′ k′l′ For each column of A, the initial value of the residual γ is y. p ;

[0069] Step S4.2 includes:

[0070] Estimating Doppler frequency shift

[0071]

[0072] in, (l i k i ) is the integer index obtained in step S4.1 The initial value of the residual γ is the time delay of the downlink signal x and the Doppler domain sensing echo y. s .

[0073] Preferably, in step S5:

[0074] Step S5.1: Calculate the estimated channel gain using the estimated time delay and Doppler parameters;

[0075] Step S5.2: Eliminate the interference of superimposed pilot signals on data symbols by detecting data symbols using the time-delay Doppler domain maximum ratio combining algorithm;

[0076] Step S5.3: Eliminate the interference of data symbols on the superimposed pilots, re-estimate the channel gain, and iterate together with step S5.2 to complete the channel estimation and data detection.

[0077] Preferably, step S5.1 includes:

[0078] Based on the relationship between the pilot signal and the original time-delay Doppler domain channel:

[0079]

[0080] Among them, y p The received signal is the Doppler domain signal with time delay after the pilot symbols have passed through the channel. L=(l max +1)(2k max +1), Its elements are the channel gain of each path;

[0081] Construct matrix B = [G1x] based on the pilot signals and the estimated time-delay Doppler domain parameters. p G2x p , ..., G P x p Because the pilot signal is superimposed on the data symbol, the receiver receives y instead of y. p Therefore, a coarse estimate of the channel gain is first obtained:

[0082]

[0083] in The channel estimation results are in vector form. This is the pseudo-inverse of matrix B;

[0084] Step S5.2 includes:

[0085] The equivalent channel matrix in the Doppler domain of the time delay is calculated based on the channel gain, and the influence of the pilot is eliminated from the received signal y, i.e.:

[0086]

[0087] To eliminate the influence of pilot signals, the received signal more closely approximates the channel's response to data symbols. Symbol detection is performed to obtain an estimate of the symbols in the time-delay Doppler domain data.

[0088] Step S5.3 includes:

[0089] Based on the estimation of data symbols Eliminate the influence of data from the received signal y, that is:

[0090]

[0091] To eliminate the influence of data, the received signal more closely approximates the channel's response to the pilot symbols. Update the sample points used to estimate the channel gain in the update step, repeat steps S5.1 and S5.2, and repeat the operation until the preset termination condition is met, exit the loop, and finally obtain the channel estimation and data demodulation results.

[0092] A sensing-assisted uplink channel estimation system based on orthogonal time-frequency regulation, provided by the present invention, includes:

[0093] Module M1: Generates pilot symbols in the time-delay Doppler domain, which are superimposed with communication data symbols to form a transmission frame;

[0094] Module M2: Converts the time-delay Doppler domain transmission frame into a time-domain uplink signal, which is transmitted by the user at the transmitting end, passes through the wireless channel, and is then converted back into a time-delay Doppler domain reception signal at the receiving end base station;

[0095] Module M3: Enables the base station to collect sensing echoes and convert the backscattered signals formed by the transmission or diffraction of the recently transmitted downlink signals by users and potential targets into the time-delay Doppler domain;

[0096] Module M4: At the receiving end, time delay and Doppler parameters are estimated using uplink pilot and sensing echo;

[0097] Module M5: Using estimated time delay and Doppler parameters, it eliminates interference between communication data and pilot symbols at the receiver, while simultaneously performing channel estimation and data detection.

[0098] Preferably in module M1:

[0099] Measure the maximum delay spread and maximum Doppler spread of the channel, and determine the relationship between channel spread and delay-Doppler domain index:

[0100]

[0101] Where, τ i , which represents the delay spread of a certain path, v i For Doppler extension, i is the index of the path, l i k is the delay axis index corresponding to the delay spread. iThe Doppler axis index corresponds to the Doppler extension; M is the number of time delay blocks in the time-delay Doppler domain planar grid, N is the number of Doppler blocks in the time-delay Doppler domain planar grid, Δf is the subcarrier frequency interval, and T is the symbol duration; the maximum time delay index l in the time-delay Doppler domain is calculated. max The maximum Doppler index is k max Randomly generate a total of N p =(2l) max +1)(4k max +1) pilot symbol;

[0102] The selected range is k∈[k p -k max k p +k max ], l∈[l p , l p +l max ], where k p ∈[0, N-1], l p ∈[0, M-1], k max For the Doppler axis index corresponding to the maximum Doppler extension, l max The delay axis index corresponding to the maximum delay extension;

[0103] The pilot symbols are superimposed one by one onto the time-delayed Doppler domain data symbols X within this range. DD superior:

[0104] X DD =X d +X p

[0105] Where X d X is a matrix-form communication data symbol. p Pilot symbols in matrix form;

[0106] In module M2:

[0107] The time-delay Doppler domain symbols are converted into time-frequency domain signals by inverse discrete symmetric Fourier transform:

[0108]

[0109] Where, x TF [m, n] represents the time-frequency domain transmitted signal, and x[k, l] is the time-delay Doppler domain symbol X. DD The elements are m = 0, 1...M-1; n = 0, 1...N-1; e is the base of the natural logarithm, and j is the imaginary unit;

[0110] The time-frequency domain symbol is transformed into a baseband time-domain signal s(t) using the Heisenberg transform:

[0111]

[0112] Where gtx(t) represents the transmitted pulse waveform, which uses rectangular transmitted and received waveforms, and inserts a cyclic prefix in the time domain to form the final transmitted signal; t indicates that the independent variable of the function is time;

[0113] s(t) can be expressed in matrix form:

[0114]

[0115] Where H is the conjugate transpose operation of the matrix; X DD Transmit signals in matrix form for the time-delay-Doppler domain; and To obtain the normalized DFT matrix, vectorize S to get s:

[0116]

[0117] in vec() is a column vectorization operation. It is the Kronecker product. To represent a complex number, I M It is an identity matrix of size M×M;

[0118] Since the channel exhibits sparsity in the time-delay Doppler domain, the complex baseband channel impulse response h(τ, v) is expressed as:

[0119]

[0120] Where P represents the number of multipath components, which is also the number of channel taps in the time-delay Doppler domain, and h i τ represents the complex channel gain of the i-th path; i Let v represent the delay of the i-th path. i Let δ represent the Doppler frequency shift of the i-th path; δ is the impulse function, τ is the time delay, and v is the Doppler frequency shift.

[0121] Delay Doppler domain channel taps and τ i v i The relationship is:

[0122]

[0123] Among them, l i With k i Let these represent the indices of the integer delay tap and the Doppler tap corresponding to the i-th path, respectively, and the fractional Doppler κ. i This represents the offset from the nearest integer tap, whose size satisfies -0.5 < κ. i≤0.5, and the relationship between the maximum channel delay spread and maximum Doppler spread and the delay-Doppler domain index is obtained as follows:

[0124]

[0125] Where, τ max For the maximum delay spread of the channel, v max For maximum Doppler extension, l max k is the delay axis index in the Doppler domain corresponding to the maximum delay spread. max The time-delay Doppler domain Doppler axis index corresponding to the maximum Doppler extension;

[0126] The signal s(t) is transmitted in the time-varying channel described above, and the received signal r(t) is given by the following equation:

[0127] r(t)=∫∫h(τ,v)s(t-τ)e j2πv(t-τ) dτdv+w(t)

[0128] Where w(t) is zero-mean additive white Gaussian noise, and its variance is...

[0129] Represent r(t) in vector form as r:

[0130] r = Hs + w

[0131] in, Let Δ be the forward cyclic shift matrix used to characterize the delay, and let Δ be a diagonal matrix. Used to characterize Doppler frequency shift

[0132] At the receiving end, the cyclic prefix is ​​first removed in the time domain, and then the signal is transformed to the time-frequency domain and the time-delay Doppler domain successively through Wigner transform and discrete symmetric Fourier transform. The above process can be represented by a matrix as follows:

[0133]

[0134] Among them, Y TF and Y DD These are the matrix forms of the received signals in the time-frequency domain and the time-delay Doppler domain, respectively, where R is the received signal matrix in the time-delay domain; for Y... DD Vectorization yields:

[0135]

[0136] in, Denotes the time-delay Doppler domain equivalent channel matrix.

[0137]

[0138] The module M3 includes:

[0139] The same operation as module M2 is performed on the sensing echo generated by the downlink signal, converting it to the time-delay Doppler domain to obtain y. s ;

[0140] In module M4:

[0141] Module M4.1: At the receiving end, extract some sampling points from the received signal in the time-delay Doppler domain, construct a sensing matrix and a vector to be reconstructed based on the known uplink pilot, and estimate the integer time-delay Doppler parameters;

[0142] Module M4.2: Sensing echo y generated from downlink signal s The fractional Doppler estimate is obtained by dividing the interval into regions within the neighborhood of the integer Doppler parameters and iteratively searching.

[0143] The module M4.1 includes:

[0144] For the received signal Y DD Extract sampling points within a given range, i.e., k∈[k p -k max k p +k max ], l∈[l p , l p +l max ], forming the measurement vector y p ;

[0145] According to the pilot matrix X p Constructing a matrix Each column ψ k′,l′ =vec(X′) p ), X′ p element x′ p [k, l] = x p ([kk′) N ,[ll′] M ), [] N and[] M These are cyclic shift operations modulo N and M, respectively, where the elements of the pilot matrix are:

[0146]

[0147] in, The power of the pilot symbol;

[0148] Get the initial Then, similarly according to the range k∈[k p -k maxk p +k max ], l∈[l p , l p +l max Extract The corresponding row, which is an M×N 0-1 matrix and its column vectorization, then the row index of 1 is the row to be extracted. The row index, after being updated, results in a smaller value.

[0149] Construct the perception matrix A:

[0150]

[0151] Where Φ is the phase offset matrix, and ⊙ represents the Hadamard product;

[0152] Searching for the column in A that best matches the current residual yields an integer time-delay Doppler index for a path, namely:

[0153]

[0154] Where ψ′ k′l′ For each column of A, the initial value of the residual γ is y. p ;

[0155] The module M4.2 includes:

[0156] Estimating Doppler frequency shift

[0157]

[0158] in, (l i k i ) is the integer index obtained from module M4.1. The initial value of the residual γ is the time delay of the downlink signal x and the Doppler domain sensing echo y. s ;

[0159] In module M5:

[0160] Module M5.1: Calculates the estimated channel gain using the estimated time delay and Doppler parameters;

[0161] Module M5.2: Eliminates interference from superimposed pilot signals on data symbols and detects data symbols using a time-delay Doppler domain maximum ratio combining algorithm;

[0162] Module M5.3: Eliminates interference from data symbols to superimposed pilots, re-estimates channel gain, and iteratively completes channel estimation and data detection together with module M5.2;

[0163] The module M5.1 includes:

[0164] Based on the relationship between the pilot signal and the original time-delay Doppler domain channel:

[0165]

[0166] Among them, y p The received signal is the Doppler domain signal with time delay after the pilot symbols have passed through the channel. L=(l max +1)(2k max +1), Its elements are the channel gain of each path;

[0167] Construct matrix B = [G1x] based on the pilot signals and the estimated time-delay Doppler domain parameters. p G2x p , ..., G P x p Because the pilot signal is superimposed on the data symbol, the receiver receives y instead of y. p Therefore, a coarse estimate of the channel gain is first obtained:

[0168]

[0169] in The channel estimation results are in vector form. This is the pseudo-inverse of matrix B;

[0170] The module M5.2 includes:

[0171] The equivalent channel matrix in the Doppler domain of the time delay is calculated based on the channel gain, and the influence of the pilot is eliminated from the received signal y, i.e.:

[0172]

[0173] To eliminate the influence of pilot signals, the received signal more closely approximates the channel's response to data symbols. Symbol detection is performed to obtain an estimate of the symbols in the time-delay Doppler domain data.

[0174] The module M5.3 includes:

[0175] Based on the estimation of data symbols Eliminate the influence of data from the received signal y, that is:

[0176]

[0177] To eliminate the influence of data, the received signal more closely approximates the channel's response to the pilot symbols. The sample points used to estimate the channel gain are updated, and modules M5.1 and S5.2 are repeated until the preset termination condition is met, then the loop is exited, and finally the channel estimation and data demodulation results are obtained.

[0178] Compared with the prior art, the present invention has the following beneficial effects:

[0179] 1. This invention proposes a channel estimation scheme based on block superimposed pilots, which can further reduce the number of sampling points required for the channel and reduce the algorithm complexity compared with schemes based on embedded pilots and full superimposed pilots. It also proposes a modified compressed sensing recovery algorithm, which can accurately estimate the fractional Doppler channel without constructing a fractional dictionary matrix, compared with the orthogonal matching pursuit (OMP) algorithm.

[0180] 2. This invention constructs a sensing-assisted uplink channel estimation system based on orthogonal time-frequency spatial waveforms. Compared to systems that only consider integer Doppler, which suffer from drastic performance degradation in fractional Doppler conditions, this system is more suitable for practical scenarios. Compared to channel estimation using only pilots, it can estimate fractional Doppler parameters more accurately, thereby improving communication performance. Compared to other orthogonal time-frequency spatial channel estimation methods, it can further reduce the number of sampling points required and lower computational complexity while ensuring the accuracy of channel estimation (fractional Doppler case). It can effectively utilize the communication sensing capabilities of orthogonal time-frequency spatial waveforms in high-mobility scenarios. Attached Figure Description

[0181] Other features, objects, and advantages of the present invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0182] Figure 1 This is a flowchart of the perception-assisted uplink channel estimation system in Embodiment 3 of the present invention;

[0183] Figure 2 This is a block diagram of the signal processing process of the system model in Embodiment 3 of the present invention;

[0184] Figure 3 This is a schematic diagram of the placement of the time-delay-Doppler domain block superimposed pilot in Embodiment 3 of the present invention;

[0185] Figure 4 The graph shows the results of comparing the channel estimation performance of the method proposed in Embodiment 3 of the present invention with other schemes.

[0186] Figure 5 This is a graph showing the comparison of the bit error rate performance of the method proposed in Embodiment 3 of the present invention with other schemes. Detailed Implementation

[0187] The present invention will now be described in detail with reference to specific embodiments. These embodiments will help those skilled in the art to further understand the present invention, but do not limit the invention in any way. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all fall within the scope of protection of the present invention.

[0188] Example 1:

[0189] A sensing-assisted uplink channel estimation method based on orthogonal time-frequency regulation, provided by the present invention, includes:

[0190] Step S1: Generate pilot symbols in the time-delay Doppler domain and superimpose them with communication data symbols to form a transmission frame;

[0191] Specifically, in step S1:

[0192] Measure the maximum delay spread and maximum Doppler spread of the channel, and determine the relationship between channel spread and delay-Doppler domain index:

[0193]

[0194] Where, τ i , which represents the delay spread of a certain path, v i For Doppler extension, i is the index of the path, l i k is the delay axis index corresponding to the delay spread. i The Doppler axis index corresponds to the Doppler extension; M is the number of time delay blocks in the time-delay Doppler domain planar grid, N is the number of Doppler blocks in the time-delay Doppler domain planar grid, Δf is the subcarrier frequency interval, and T is the symbol duration; the maximum time delay index l in the time-delay Doppler domain is calculated. max The maximum Doppler index is k max Randomly generate a total of N p =(2l) max +1)(4k max +1) pilot symbol;

[0195] The selected range is k∈[k p -k max k p +k max ], l∈[l p , l p +l max ], where k p ∈[0, N-1], l p ∈[0, M-1], k max For the Doppler axis index corresponding to the maximum Doppler extension, l maxThe delay axis index corresponding to the maximum delay extension;

[0196] The pilot symbols are superimposed one by one onto the time-delayed Doppler domain data symbols X within this range. DD superior:

[0197] X DD =X d +X p

[0198] Where X d X is a matrix-form communication data symbol. p The pilot symbols are in matrix form.

[0199] Step S2: Convert the time-delay Doppler domain transmission frame into a time-domain uplink signal, transmit it through the transmitting end user, and after passing through the wireless channel, convert it back into a time-delay Doppler domain reception signal at the receiving end base station;

[0200] Specifically, in step S2:

[0201] The time-delay Doppler domain symbols are converted into time-frequency domain signals by inverse discrete symmetric Fourier transform:

[0202]

[0203] Where, x TF [m, n] represents the time-frequency domain transmitted signal, and x[k, l] is the time-delay Doppler domain symbol X. DD The elements are m = 0, 1...M-1; n = 0, 1...N-1; e is the base of the natural logarithm, and j is the imaginary unit;

[0204] The time-frequency domain symbol is transformed into a baseband time-domain signal s(t) using the Heisenberg transform:

[0205]

[0206] Where gtx(t) represents the transmitted pulse waveform, which uses rectangular transmitted and received waveforms, and inserts a cyclic prefix in the time domain to form the final transmitted signal; t indicates that the independent variable of the function is time;

[0207] s(t) can be expressed in matrix form:

[0208]

[0209] Where H is the conjugate transpose operation of the matrix; X DD Transmit signals in matrix form for the time-delay-Doppler domain; and To obtain the normalized DFT matrix, vectorize S to get s:

[0210]

[0211] in, vec() is a column vectorization operation. It is the Kronecker product. To represent a complex number, I M It is an identity matrix of size M×M;

[0212] Since the channel exhibits sparsity in the time-delay Doppler domain, the complex baseband channel impulse response h(τ, v) is expressed as:

[0213]

[0214] Where P represents the number of multipath components, which is also the number of channel taps in the time-delay Doppler domain, and h i τ represents the complex channel gain of the i-th path; i Let v represent the delay of the i-th path. i Let δ represent the Doppler frequency shift of the i-th path; δ is the impulse function, τ is the time delay, and v is the Doppler frequency shift.

[0215] Delay Doppler domain channel taps and τ i v i The relationship is:

[0216]

[0217] Among them, l i With k i Let these represent the indices of the integer delay tap and the Doppler tap corresponding to the i-th path, respectively, and the fractional Doppler κ. i This represents the offset from the nearest integer tap, whose size satisfies -0.5 < κ. i ≤0.5, and the relationship between the maximum channel delay spread and maximum Doppler spread and the delay-Doppler domain index is obtained as follows:

[0218]

[0219] Where, τ max For the maximum delay spread of the channel, v max For maximum Doppler extension, l max k is the delay axis index in the Doppler domain corresponding to the maximum delay spread. max The time-delay Doppler domain Doppler axis index corresponding to the maximum Doppler extension;

[0220] The signal s(t) is transmitted in the time-varying channel described above, and the received signal r(t) is given by the following equation:

[0221] r(t)=∫∫h(τ,v)s(t-τ)e j2πv(t-τ) dτdv+w(t)

[0222] Where w(t) is zero-mean additive white Gaussian noise, and its variance is...

[0223] Represent r(t) in vector form as r:

[0224] r = Hs + w

[0225] in, Let Δ be the forward cyclic shift matrix used to characterize the delay, and let Δ be a diagonal matrix. Used to characterize Doppler frequency shift

[0226] At the receiving end, the cyclic prefix is ​​first removed in the time domain, and then the signal is transformed to the time-frequency domain and the time-delay Doppler domain successively through Wigner transform and discrete symmetric Fourier transform. The above process can be represented by a matrix as follows:

[0227]

[0228] Among them, Y TF and Y DD These are the matrix forms of the received signals in the time-frequency domain and the time-delay Doppler domain, respectively, where R is the received signal matrix in the time-delay domain; for Y... DD Vectorization yields:

[0229]

[0230] in, Denotes the time-delay Doppler domain equivalent channel matrix.

[0231]

[0232] Step S3: Instruct the base station to collect sensing echoes and convert the backscattered signals formed by the transmission or diffraction of the recently transmitted downlink signals by users and potential targets into the time-delay Doppler domain;

[0233] Step S3 includes:

[0234] The same operation as in step S2 is performed on the sensing echo generated by the downlink signal, converting it to the time-delay Doppler domain to obtain y. s .

[0235] Step S4: At the receiving end, time delay and Doppler parameters are estimated using uplink pilot and sensing echo;

[0236] Specifically, in step S4:

[0237] Step S4.1: At the receiving end, extract some sampling points from the received signal in the time-delay Doppler domain, construct the sensing matrix and the vector to be reconstructed based on the known uplink pilot, and estimate the integer time-delay Doppler parameters;

[0238] Step S4.2: Utilize the sensing echo y formed by the downlink signal s The fractional Doppler estimate is obtained by iteratively searching within the neighborhood of the integer Doppler parameters.

[0239] Specifically, step S4.1 includes:

[0240] For the received signal Y DD Extract sampling points within a given range, i.e., k∈[k p -k max k p +k max ], l∈[l p , l p +l max ], forming the measurement vector y p ;

[0241] According to the pilot matrix X p Constructing a matrix Each column ψ k′，l′ =vec(X′) p ), X′ p element x′ p [k, l] = x p ([kk′) N ,[ll′] M ), [] N and[] M These are cyclic shift operations modulo N and M, respectively, where the elements of the pilot matrix are:

[0242]

[0243] in, The power of the pilot symbol;

[0244] Get the initial Then, similarly according to the range k∈[k p -k max k p +k max ], l∈[l p , l p +l max Extract The corresponding row, which is an M×N 0-1 matrix and its column vectorization, then the row index of 1 is the row to be extracted. The row index, after being updated, results in a smaller value.

[0245] Construct the perception matrix A:

[0246]

[0247] Where Φ is the phase offset matrix, and ⊙ represents the Hadamard product;

[0248] Searching for the column in A that best matches the current residual yields an integer time-delay Doppler index for a path, namely:

[0249]

[0250] Where ψ′ k′l′ For each column of A, the initial value of the residual γ is y. p ;

[0251] Step S4.2 includes:

[0252] Estimating Doppler frequency shift

[0253]

[0254] in, (l i k i ) is the integer index obtained in step S4.1 The initial value of the residual γ is the time delay of the downlink signal x and the Doppler domain sensing echo y. s .

[0255] Step S5: Using the estimated time delay and Doppler parameters, eliminate the interference between communication data and pilot symbols at the receiving end, and simultaneously perform channel estimation and data detection.

[0256] Specifically, in step S5:

[0257] Step S5.1: Calculate the estimated channel gain using the estimated time delay and Doppler parameters;

[0258] Step S5.2: Eliminate the interference of superimposed pilot signals on data symbols by detecting data symbols using the time-delay Doppler domain maximum ratio combining algorithm;

[0259] Step S5.3: Eliminate the interference of data symbols on the superimposed pilots, re-estimate the channel gain, and iterate together with step S5.2 to complete the channel estimation and data detection.

[0260] Specifically, step S5.1 includes:

[0261] Based on the relationship between the pilot signal and the original time-delay Doppler domain channel:

[0262]

[0263] Among them, y p The received signal is the Doppler domain signal with time delay after the pilot symbols have passed through the channel. L=(l max +1)(2k max +1), Its elements are the channel gain of each path;

[0264] Construct matrix B = [G1x] based on the pilot signals and the estimated time-delay Doppler domain parameters. p G2x p , ..., G P x p Because the pilot signal is superimposed on the data symbol, the receiver receives y instead of y. p Therefore, a coarse estimate of the channel gain is first obtained:

[0265]

[0266] in The channel estimation results are in vector form. This is the pseudo-inverse of matrix B;

[0267] Step S5.2 includes:

[0268] The equivalent channel matrix in the Doppler domain of the time delay is calculated based on the channel gain, and the influence of the pilot is eliminated from the received signal y, i.e.:

[0269]

[0270] To eliminate the influence of pilot signals, the received signal more closely approximates the channel's response to data symbols. Symbol detection is performed to obtain an estimate of the symbols in the time-delay Doppler domain data.

[0271] Step S5.3 includes:

[0272] Based on the estimation of data symbols Eliminate the influence of data from the received signal y, that is:

[0273]

[0274] To eliminate the influence of data, the received signal more closely approximates the channel's response to the pilot symbols. Update the sample points used to estimate the channel gain in the update step, repeat steps S5.1 and S5.2, and repeat the operation until the preset termination condition is met, exit the loop, and finally obtain the channel estimation and data demodulation results.

[0275] Example 2:

[0276] Example 2 is a preferred embodiment of Example 1, and is used to illustrate the present invention in more detail.

[0277] The present invention also provides a sensing-assisted uplink channel estimation system based on orthogonal time-frequency air conditioning. The sensing-assisted uplink channel estimation system based on orthogonal time-frequency air conditioning can be implemented by executing the process steps of the sensing-assisted uplink channel estimation method based on orthogonal time-frequency air conditioning. That is, those skilled in the art can understand the sensing-assisted uplink channel estimation method based on orthogonal time-frequency air conditioning as a preferred embodiment of the sensing-assisted uplink channel estimation system based on orthogonal time-frequency air conditioning.

[0278] A sensing-assisted uplink channel estimation system based on orthogonal time-frequency regulation, provided by the present invention, includes:

[0279] Module M1: Generates pilot symbols in the time-delay Doppler domain, which are superimposed with communication data symbols to form a transmission frame;

[0280] In module M1:

[0281] Measure the maximum delay spread and maximum Doppler spread of the channel, and determine the relationship between channel spread and delay-Doppler domain index:

[0282]

[0283] Where, τ i , which represents the delay spread of a certain path, v i For Doppler extension, i is the index of the path, l i k is the delay axis index corresponding to the delay spread. i The Doppler axis index corresponds to the Doppler extension; M is the number of time delay blocks in the time-delay Doppler domain planar grid, N is the number of Doppler blocks in the time-delay Doppler domain planar grid, Δf is the subcarrier frequency interval, and T is the symbol duration; the maximum time delay index l in the time-delay Doppler domain is calculated. max The maximum Doppler index is k max Randomly generate a total of N p =(2l) max +1)(4k max +1) pilot symbol;

[0284] The selected range is k∈[k p -k max kp +k max ], l∈[l p , l p +l max ], where k p ∈[0, N-1], l p ∈[0, M-1], k max For the Doppler axis index corresponding to the maximum Doppler extension, l max The delay axis index corresponding to the maximum delay extension;

[0285] The pilot symbols are superimposed one by one onto the time-delayed Doppler domain data symbols X within this range. DD superior:

[0286] X DD =X d +X p

[0287] Where X d X is a matrix-form communication data symbol. p Pilot symbols in matrix form;

[0288] Module M2: Converts the time-delay Doppler domain transmission frame into a time-domain uplink signal, which is transmitted by the user at the transmitting end, passes through the wireless channel, and is then converted back into a time-delay Doppler domain reception signal at the receiving end base station;

[0289] In module M2:

[0290] The time-delay Doppler domain symbols are converted into time-frequency domain signals by inverse discrete symmetric Fourier transform:

[0291]

[0292] Where, x TF [m, n] represents the time-frequency domain transmitted signal, and x[k, l] is the time-delay Doppler domain symbol X. DD The elements are m = 0, 1...M-1; n = 0, 1...N-1; e is the base of the natural logarithm, and j is the imaginary unit;

[0293] The time-frequency domain symbol is transformed into a baseband time-domain signal s(t) using the Heisenberg transform:

[0294]

[0295] Among them, g tx (t) represents the transmitted pulse waveform, using rectangular transmitted and received waveforms, with a cyclic prefix inserted in the time domain to form the final transmitted signal; t indicates that the independent variable of the function is time;

[0296] s(t) can be expressed in matrix form:

[0297]

[0298] Where H is the conjugate transpose operation of the matrix; X DD Transmit signals in matrix form for the time-delay-Doppler domain; and To obtain the normalized DFT matrix, vectorize S to get s:

[0299]

[0300] in, vec() is a column vectorization operation. It is the Kronecker product. To represent a complex number, I M It is an identity matrix of size M×M;

[0301] Since the channel exhibits sparsity in the time-delay Doppler domain, the complex baseband channel impulse response h(τ, v) is expressed as:

[0302]

[0303] Where P represents the number of multipath components, which is also the number of channel taps in the time-delay Doppler domain, and h i τ represents the complex channel gain of the i-th path; i Let v represent the delay of the i-th path. i Let δ represent the Doppler frequency shift of the i-th path; δ is the impulse function, τ is the time delay, and v is the Doppler frequency shift.

[0304] Delay Doppler domain channel taps and τ i v i The relationship is:

[0305]

[0306] Among them, l i With k i Let these represent the indices of the integer delay tap and the Doppler tap corresponding to the i-th path, respectively, and the fractional Doppler κ. i This represents the offset from the nearest integer tap, whose size satisfies -0.5 < κ. i ≤0.5, and the relationship between the maximum channel delay spread and maximum Doppler spread and the delay-Doppler domain index is obtained as follows:

[0307]

[0308] Where, τ max V is the maximum delay spread of the channel. max For maximum Doppler extension, l maxk is the delay axis index in the Doppler domain corresponding to the maximum delay spread. max The time-delay Doppler domain Doppler axis index corresponding to the maximum Doppler extension;

[0309] The signal s(t) is transmitted in the time-varying channel described above, and the received signal r(t) is given by the following equation:

[0310] r(t)=∫∫h(τ,v)s(t-τ)e j2πv(t-τ) dτdv+w(t)

[0311] Where w(t) is zero-mean additive white Gaussian noise, and its variance is...

[0312] Represent r(t) in vector form as r:

[0313] r = Hs + w

[0314] in, Let Δ be the forward cyclic shift matrix used to characterize the delay, and let Δ be a diagonal matrix. Used to characterize Doppler frequency shift

[0315] At the receiving end, the cyclic prefix is ​​first removed in the time domain, and then the signal is transformed to the time-frequency domain and the time-delay Doppler domain successively through Wigner transform and discrete symmetric Fourier transform. The above process can be represented by a matrix as follows:

[0316]

[0317] Among them, Y TF and Y DD These are the matrix forms of the received signals in the time-frequency domain and the time-delay Doppler domain, respectively, where R is the received signal matrix in the time-delay domain; for Y... DD Vectorization yields:

[0318]

[0319] in, Denotes the time-delay Doppler domain equivalent channel matrix.

[0320]

[0321] Module M3: Enables the base station to collect sensing echoes and convert the backscattered signals formed by the transmission or diffraction of the recently transmitted downlink signals by users and potential targets into the time-delay Doppler domain;

[0322] The module M3 includes:

[0323] The same operation as module M2 is performed on the sensing echo generated by the downlink signal, converting it to the time-delay Doppler domain to obtain y. s ;

[0324] Module M4: At the receiving end, time delay and Doppler parameters are estimated using uplink pilot and sensing echo;

[0325] In module M4:

[0326] Module M4.1: At the receiving end, extract some sampling points from the received signal in the time-delay Doppler domain, construct a sensing matrix and a vector to be reconstructed based on the known uplink pilot, and estimate the integer time-delay Doppler parameters;

[0327] Module M4.2: Sensing echo y generated from downlink signal s The fractional Doppler estimate is obtained by dividing the interval into regions within the neighborhood of the integer Doppler parameters and iteratively searching.

[0328] The module M4.1 includes:

[0329] For the received signal Y DD Extract sampling points within a given range, i.e., k∈[k p -k max k p +k max ], l∈[l p , l p +l max ], forming the measurement vector y p ;

[0330] According to the pilot matrix X p Constructing a matrix Each column ψ k′,l′ =vec(X′) p ), X′ p element x′ p [k, l] = x p ([kk′) N ,[ll′] M ), [] N and[] M These are cyclic shift operations modulo N and M, respectively, where the elements of the pilot matrix are:

[0331]

[0332] in, The power of the pilot symbol;

[0333] Get the initial Then, similarly according to the range k∈[k p -kmax k p +k max ], l∈[l p , l p +l max Extract The corresponding row, which is an M×N 0-1 matrix and its column vectorization, then the row index of 1 is the row to be extracted. The row index, after being updated, results in a smaller value.

[0334] Construct the perception matrix A:

[0335]

[0336] Where Φ is the phase offset matrix, and ⊙ represents the Hadamard product;

[0337] Searching for the column in A that best matches the current residual yields an integer time-delay Doppler index for a path, namely:

[0338]

[0339] Where ψ′ k′,l′ For each column of A, the initial value of the residual γ is y. p ;

[0340] The module M4.2 includes:

[0341] Estimating Doppler frequency shift

[0342]

[0343] in, (l i k i ) is the integer index obtained from module M4.1. The initial value of the residual γ is the time delay of the downlink signal x and the Doppler domain sensing echo y. s ;

[0344] Module M5: Using estimated time delay and Doppler parameters, it eliminates interference between communication data and pilot symbols at the receiver, while simultaneously performing channel estimation and data detection.

[0345] In module M5:

[0346] Module M5.1: Calculates the estimated channel gain using the estimated time delay and Doppler parameters;

[0347] Module M5.2: Eliminates interference from superimposed pilot signals on data symbols and detects data symbols using a time-delay Doppler domain maximum ratio combining algorithm;

[0348] Module M5.3: Eliminates interference from data symbols to superimposed pilots, re-estimates channel gain, and iteratively completes channel estimation and data detection together with module M5.2;

[0349] The module M5.1 includes:

[0350] Based on the relationship between the pilot signal and the original time-delay Doppler domain channel:

[0351]

[0352] Among them, y p The received signal is the Doppler domain signal with time delay after the pilot symbols have passed through the channel. L=(l max +1)(2k max +1), Its elements are the channel gain of each path;

[0353] Construct matrix B = [G1x] based on the pilot signals and the estimated time-delay Doppler domain parameters. p G2x p , ..., G P x p Because the pilot signal is superimposed on the data symbol, the receiver receives y instead of y. p Therefore, a coarse estimate of the channel gain is first obtained:

[0354]

[0355] in The channel estimation results are in vector form. This is the pseudo-inverse of matrix B;

[0356] The module M5.2 includes:

[0357] The equivalent channel matrix in the Doppler domain of the time delay is calculated based on the channel gain, and the influence of the pilot is eliminated from the received signal y, i.e.:

[0358]

[0359] To eliminate the influence of pilot signals, the received signal more closely approximates the channel's response to data symbols. Symbol detection is performed to obtain an estimate of the symbols in the time-delay Doppler domain data.

[0360] The module M5.3 includes:

[0361] Based on the estimation of data symbols Eliminate the influence of data from the received signal y, that is:

[0362]

[0363] To eliminate the influence of data, the received signal more closely approximates the channel's response to the pilot symbols. The sample points used to estimate the channel gain are updated, and modules M5.1 and S5.2 are repeated until the preset termination condition is met, then the loop is exited, and finally the channel estimation and data demodulation results are obtained.

[0364] Example 3:

[0365] Example 3 is a preferred example of Example 1, and is used to illustrate the present invention in more detail.

[0366] Reference Figure 1 and Figure 2 As shown, this invention provides a sensing-assisted uplink channel estimation method based on orthogonal time-frequency air conditioning, comprising:

[0367] Step S1: Generate pilot symbols in the delay-Doppler domain and superimpose them with communication data symbols to form a transmission frame;

[0368] Step S2: Convert the time-delay-Doppler domain transmission frame into a time-domain uplink signal, transmit it through the transmitting end (user), and after passing through the wireless channel, convert it back into a time-delay-Doppler domain reception signal at the receiving end (base station);

[0369] Step S3: The base station collects the sensing echo, which is the backscattered signal formed by the transmission or diffraction of the recently transmitted downlink signal by the communication user and potential target objects;

[0370] Step S4: At the receiving end, time delay and Doppler parameters are estimated using uplink pilot and sensing echo;

[0371] Step S5: At the receiving end, eliminate the interference between communication data and pilot symbols, and simultaneously perform channel estimation and data detection.

[0372] The above are basic embodiments of the present invention. The technical solution of the present invention will be further described below through a preferred embodiment.

[0373] Measure the maximum delay spread and maximum Doppler spread of the channel, and determine the relationship between channel spread and delay-Doppler domain index. (Where M and N are the number of delay blocks and Doppler blocks in the delay-Doppler domain planar grid, respectively, and Δf and T are the subcarrier frequency spacing and symbol duration, respectively.) The maximum delay index l in the delay-Doppler domain is calculated. max The maximum Doppler index is k max Randomly generate a total of N p =(2l)max +1)(4k max +1) pilot symbol;

[0374] Reference Figure 3 As shown, the selected range is k∈[k p -k max k p +k max ], l∈[l p , l p +l max ], where k p ∈[0, N-1], l p ∈[0, M-1], the generated pilot symbols are superimposed one by one onto the time-delay-Doppler domain data symbols within this range, i.e.

[0375] X DD =X d +X p

[0376] Where X d and X p These represent the communication data symbols and pilot symbols in matrix form, respectively;

[0377] The time-delay-Doppler domain symbols are converted into time-frequency domain signals by using the inverse discrete symmetric Fourier transform:

[0378]

[0379] Where x TF [m, n] represents the time-frequency domain transmitted signal, and x[k, l] is the time-delay-Doppler domain symbol X. DD The elements are m = 0, 1...M-1, n = 0, 1...N-1. e is the base of the natural logarithm, and j is the imaginary unit.

[0380] The time-frequency domain symbol is transformed into a baseband time-domain signal using the Heisenberg transform:

[0381]

[0382] Wherein, gtx(t) represents the transmitted pulse waveform (a rectangular transmitted and received waveform is used in this invention), and finally a cyclic prefix is ​​inserted in the time domain to form the final transmitted signal;

[0383] s(t) can be represented in matrix form. in and To obtain the normalized DFT matrix, vectorize S to get... in vec() is a column vectorization operation. It is the Kronecker product. To represent a complex number, I M It is an identity matrix of size M×M;

[0384] Since the channel exhibits sparsity in the time-delay-Doppler domain, the complex baseband channel impulse response can be expressed as:

[0385]

[0386] Where P represents the number of multipath components, also known as the number of time delay-Doppler domain channel taps, h i , τ i v i Let represent the complex channel gain, time delay, and Doppler shift of the i-th path, respectively. The time delay-Doppler domain channel tap and τ i v i The relationship is:

[0387]

[0388] Among them, l i With k i Let these represent the indices of the integer delay tap and the Doppler tap corresponding to the i-th path, respectively, and the fractional Doppler κ. i This represents the offset from the nearest integer tap, whose size satisfies -0.5 < κ. i ≤0.5, and the relationship between the maximum channel delay spread and maximum Doppler spread and the delay-Doppler domain index can be obtained as follows:

[0389] The signal s(t) is transmitted in the time-varying channel described above, and the received signal r(t) is given by the following equation:

[0390] r(t)=∫∫h(τ,v)s(t-τ)e j2πv(t-τ) dτdv+w(t)

[0391] Where w(t) is zero-mean additive white Gaussian noise, and its variance is...

[0392] Represent r(t) in vector form as follows:

[0393] r = Hs + w

[0394] in Let Δ be the forward cyclic shift matrix used to characterize the delay, and let Δ be a diagonal matrix. Used to characterize Doppler frequency shift

[0395] At the receiving end, the cyclic prefix is ​​first removed in the time domain, and then the signal is transformed to the time-frequency domain and the time-delay-Doppler domain successively through Wigner transform and discrete symmetric Fourier transform. The above process can be represented by a matrix as follows:

[0396]

[0397] Where Y TF and Y DD The matrix forms of the received signals in the time-frequency domain and the time-delay Doppler domain are respectively given for Y. DD Vectorization yields:

[0398]

[0399] in The time-delay-Doppler equivalent channel matrix is ​​denoted as the time-delay-Doppler domain equivalent channel matrix.

[0400] The same operation is performed on the sensing echo generated by the downlink signal, converting it to the time-delay-Doppler domain to obtain y. s .

[0401] For the received signal Y DD Extract sampling points within a given range, i.e., k∈[k p -k max k p +k max ], l∈[l p , l p +l max ], forming the measurement vector y p ;

[0402] According to the pilot matrix X p Constructing a matrix Each column ψ k′，l′ =vec(X′) p ), X′ p element x′ p [k, l] = x p ([kk′) N ,[ll′] M ), [] N and[] M These are cyclic shift operations modulo N and M, respectively, where the elements of the pilot matrix are:

[0403]

[0404] in The power of the pilot symbol;

[0405] Get the initial Then, similarly according to the range k∈[k p -k max k p +k max ], l∈[l p , l p +l max Extract Specifically, if we consider this range as an M×N 0-1 matrix and vectorize its columns, then the row index containing the "1" is the row index to be extracted. The row index, after being updated, results in a smaller value.

[0406] Constructing a perception matrix Where Φ is the phase offset matrix, and ⊙ represents the Hadamard product;

[0407] Searching for the column in A that best matches the current residual yields an integer time-delay Doppler index for a path, namely:

[0408]

[0409] Where ψ′ k′l′ For each column of A, the initial value of the residual γ1 is y. p ;

[0410] The Doppler frequency shift can be estimated using the following formula:

[0411]

[0412] in (l i k i ) is the integer index obtained in the previous step. The initial value of the residual γ2 is the time delay of the downlink signal x - Doppler domain sensing echo y. s Specifically, an iterative search method is used. In each iteration, the search interval (the initial search interval is Ω) is calculated. i Choose two points v1 = v l +η(v u -v l ) and v2 = v l +(1-η)(v u -v l ), where η is a constant factor used to divide the interval, v u and v l Let v be the left and right endpoints of the current interval, and v be the length of the interval. u -v lConstruct vectors G1x and G2x associated with these two points, calculate and compare the correlation between these two vectors and the current residual, and use the points with higher correlation as the endpoints of the new search interval to continue the search. More specifically, the Fibonacci sequence is used to determine the selected points, i.e.:

[0413]

[0414] in Factors that divide the interval n is the current iteration number, initially set to 1. The iteration count is repeated, and after each iteration, the estimated Doppler frequency shift v is obtained, which is the midpoint of the search interval.

[0415] Note that the above iterative search only estimates the Doppler shift of one multipath channel component. To estimate the parameters of all multipaths, an outer loop is set up. In each loop, the sensing matrix constructed from the pilots is used to search for one multipath component, determine the integer time delay and Doppler index, and then the actual Doppler shift (i.e., fractional Doppler) is estimated with the help of the sensing echo. Finally, the residuals γ1 and γ2 need to be updated to eliminate the influence of the current multipath component in the entire signal and prevent it from being searched repeatedly in the next loop. In addition, considering that the uplink signal and the sensing echo do not experience the exact same fading, the update of residual γ2 should be performed separately from γ1. The specific operations are as follows:

[0416]

[0417] Where Ψ1 = G i x p Ψ2=G i x represents the current multipath component calculated based on the estimated time delay-Doppler parameters in each iteration.

[0418] The outer loop uses a conditional statement ||γ1||>ε to control whether the loop continues, where For the aforementioned noise variance, a threshold ε is used as a criterion to indicate whether all multipath components have been searched. After the outer loop completes, the integer time delay and fractional Doppler parameters corresponding to all multipaths are obtained.

[0419] Based on the relationship between the pilot signal and the original time-delay-Doppler domain channel:

[0420]

[0421] Where y p The received signal is the time-delay-Doppler domain signal after the pilot symbols have traveled through the channel. L=(l max +1)(2k max+1), where each column is Ψ1 obtained from the outer loop mentioned above. Its elements are the channel gain of each path;

[0422] Construct matrix B = [G1x] based on the pilot signals and the estimated time-delay-Doppler domain parameters. p G2x p , ..., G P X p Because the pilot signal is superimposed on the data symbol, the receiver can only obtain y instead of y. p Therefore, we first roughly estimate the channel gain:

[0423]

[0424] The time-delay-Doppler domain equivalent channel matrix is ​​calculated based on the channel gain, and the influence of the pilot is eliminated from the received signal y, i.e.:

[0425]

[0426] right Symbol detection is performed using the Maximum Ratio Combining (MRC) algorithm to obtain estimates of the time-delay-Doppler domain data symbols.

[0427] Based on the estimation of data symbols Eliminate the influence of data from the received signal y, that is:

[0428]

[0429] by The update step estimates the sample points used for channel gain estimation, and then performs channel estimation and data detection again, repeating the operation until a certain termination condition is met (such as the iteration has reached the maximum set number of rounds, or the change in the result of this round of iteration estimation compared to the previous round is less than the set threshold, which can be considered as the convergence of the iterative algorithm). The loop is then exited, and the channel estimation and data demodulation results are finally obtained.

[0430] Reference Figure 4 and Figure 5 As shown, under the same fractional Doppler channel simulation parameters, the channel estimation accuracy and bit error rate of the proposed method are better than those of schemes that only consider integer Doppler, schemes that only use uplink pilots without using sensing information, and schemes that do not use iterative interference cancellation. The channel estimation accuracy is slightly lower than that of the embedded pilot scheme using sensing assistance, because the embedded pilot is not affected by data symbols at all. However, the obvious drawback is that the pilot occupies spectrum resources, resulting in lower spectrum efficiency than the proposed method. Furthermore, because the pilot prevents data symbols from obtaining full delay-Doppler domain diversity gain, the bit error rate is higher than that of the proposed method.

[0431] This invention also provides a sensing-assisted uplink channel estimation system based on orthogonal time-frequency air conditioning, comprising:

[0432] Module M1: Generates pilot symbols in the delay-Doppler domain, which are superimposed with communication data symbols to form a transmission frame.

[0433] The system model in module M1 includes:

[0434] Measure the maximum delay spread and maximum Doppler spread of the channel, and determine the relationship between channel spread and delay-Doppler domain index. (Where M and N are the number of delay blocks and Doppler blocks in the delay-Doppler domain planar grid, respectively, and Δf and T are the subcarrier frequency spacing and symbol duration, respectively.) The maximum delay index l in the delay-Doppler domain is calculated. max The maximum Doppler index is k max The total number of N is randomly generated using 4-QAM digital modulation. p =(2l) max +1)(4k max +1) pilot symbol;

[0435] The selected range is k∈[k p -k max k p +k max ], l∈[l p , l p +l max ], where k p ∈[0, N-1], l p ∈[0, M-1], the pilot symbols are superimposed one by one onto the time-delay-Doppler domain data symbols within this range, i.e.

[0436] X DD =X d +X p

[0437] Where X d and X p These represent the communication data symbols and pilot symbols in matrix form, respectively.

[0438] Module M2: Converts the time-delay-Doppler domain transmission frame into a time-domain uplink signal, which is then transmitted by the transmitting end (user), passes through the wireless channel, and is converted back into a time-delay-Doppler domain reception signal at the receiving end (base station).

[0439] The system model in module M2 includes:

[0440] The time-delay-Doppler domain symbols are converted into time-frequency domain signals by using the inverse discrete symmetric Fourier transform:

[0441]

[0442] Where x TF [m, n] represents the time-frequency domain transmitted signal, and x[k, l] is the time-delay-Doppler domain symbol X. DD The elements are m = 0, 1...M-1, n = 0, 1...N-1. e is the base of the natural logarithm, and j is the imaginary unit.

[0443] The time-frequency domain symbol is transformed into a baseband time-domain signal using the Heisenberg transform:

[0444]

[0445] Among them, g tx (t) represents the transmitted pulse waveform (a rectangular transmitted and received waveform is used in this invention), and finally a cyclic prefix is ​​inserted in the time domain to form the final transmitted signal;

[0446] s(t) can be represented in matrix form. in and To obtain the normalized DFT matrix, vectorize S to get... in vec() is a column vectorization operation. It is the Kronecker product. To represent a complex number, I M It is an identity matrix of size M×M;

[0447] Since the channel exhibits sparsity in the time-delay-Doppler domain, the complex baseband channel impulse response can be expressed as:

[0448]

[0449] Where P represents the number of multipath components, also known as the number of time delay-Doppler domain channel taps, h i , τ i v i Let represent the complex channel gain, time delay, and Doppler shift of the i-th path, respectively. The time delay-Doppler domain channel tap and τ i v i The relationship is:

[0450]

[0451] Among them, l i With k i Let these represent the indices of the integer delay tap and the Doppler tap corresponding to the i-th path, respectively, and the fractional Doppler κ. i This represents the offset from the nearest integer tap, whose size satisfies -0.5 < κ. i≤0.5, and the relationship between the maximum channel delay spread and maximum Doppler spread and the delay-Doppler domain index can be obtained as follows:

[0452] The signal s(t) is transmitted in the time-varying channel described above, and the received signal r(t) is given by the following equation:

[0453] r(t)=∫∫h(τ,v)s(t-τ)e j2πv(t-τ) dτdv+w(t)

[0454] Where w(t) is zero-mean additive white Gaussian noise, and its variance is...

[0455] Represent r(t) in vector form as follows:

[0456] r = Hs + w

[0457] in Let Δ be the forward cyclic shift matrix used to characterize the delay, and let Δ be a diagonal matrix. Used to characterize Doppler frequency shift

[0458] At the receiving end, the cyclic prefix is ​​first removed in the time domain, and then the signal is transformed to the time-frequency domain and the time-delay-Doppler domain successively through Wigner transform and discrete symmetric Fourier transform. The above process can be represented by a matrix as follows:

[0459]

[0460] Where Y TF and Y DD The matrix forms of the received signals in the time-frequency domain and the time-delay Doppler domain are respectively given for Y. DD Vectorization yields:

[0461]

[0462] in The time-delay-Doppler equivalent channel matrix is ​​denoted as the time-delay-Doppler domain equivalent channel matrix.

[0463] Module M3: The base station collects sensing echoes, which are backscattered signals formed by the transmission or diffraction of the most recently transmitted downlink signal by communication users and potential targets.

[0464] Module M3 specifically includes:

[0465] The same operation is performed on the sensing echo generated by the downlink signal, converting it to the time-delay-Doppler domain to obtain y. s .

[0466] Module M4: At the receiver end, time delay and Doppler parameters are estimated using uplink pilot and sensing echo.

[0467] The M4 module model includes:

[0468] Module M4.1: At the receiving end, extract some sampling points from the received signal in the time-delay-Doppler domain, construct a sensing matrix and a vector to be reconstructed based on the known uplink pilot, and estimate the integer time-delay Doppler parameters;

[0469] Specifically, module M4.1 includes:

[0470] For the received signal Y DD Extract sampling points within a given range, i.e., k∈[k p -k max k p +k max ], l∈[l p , l p +l max ], forming the measurement vector y p ;

[0471] According to the pilot matrix X p Constructing a matrix Each column ψ k′,l′ =vec(X′) p ), X′ p element x′ p [k, l] = x p ([kk′) N ,[ll′] M ), [] N and[] M These are cyclic shift operations modulo N and M, respectively, where the elements of the pilot matrix are:

[0472]

[0473] in The power of the pilot symbol;

[0474] Get the initial Then, similarly according to the range k∈[k p -k max k p +k max ], l∈[l p , l p +l max Extract Specifically, if we consider this range as an M×N 0-1 matrix and vectorize its columns, then the row index containing the "1" is the row index to be extracted. The row index, after being updated, results in a smaller value.

[0475] Constructing a perception matrix Where Φ is the phase offset matrix, and ⊙ represents the Hadamard product;

[0476] Searching for the column in A that best matches the current residual yields an integer time-delay Doppler index for a path, namely:

[0477]

[0478] Where ψ′ k′l′ For each column of A, the initial value of the residual γ1 is y. p ;

[0479] Module M4.2: Sensing echo y generated from downlink signal s The fractional Doppler estimate is obtained by iteratively searching within the neighborhood of the integer Doppler parameters.

[0480] Specifically, module M4.2 includes:

[0481] The Doppler frequency shift can be estimated using the following formula:

[0482]

[0483] in (l i k i ) is the integer index obtained in the previous step. The initial value of the residual γ2 is the time delay of the downlink signal x - Doppler domain sensing echo y. s Specifically, an iterative search method is used. In each iteration, the search interval (the initial search interval is Ω) is calculated. i Choose two points v1 = v l +η(v u -v l ) and v2 = v l +(1-η)(v u -v f ), where η is a constant factor used to divide the interval, v u and v l Let v be the left and right endpoints of the current interval, and v be the length of the interval. u -v l Construct vectors G1x and G2x associated with these two points, calculate and compare the correlation between these two vectors and the current residual, and use the points with higher correlation as the endpoints of the new search interval to continue the search. More specifically, the Fibonacci sequence is used to determine the selected points, i.e.:

[0484]

[0485] in Factors that divide the interval n is the current iteration number, initially set to 1. The iteration count is repeated until the iteration stops, at which point the estimated Doppler frequency shift v is obtained, which is the midpoint of the search interval.

[0486] Note that the above iterative search only estimates the Doppler shift of one multipath channel component. To estimate the parameters of all multipaths, an outer loop is set up. In each loop, the sensing matrix constructed from the pilots is used to search for one multipath component, determine the integer time delay and Doppler index, and then the actual Doppler shift (i.e., fractional Doppler) is estimated with the help of the sensing echo. Finally, the residuals γ1 and γ2 need to be updated to eliminate the influence of the current multipath component in the entire signal and prevent it from being searched repeatedly in the next loop. In addition, considering that the uplink signal and the sensing echo do not experience the exact same fading, the update of residual γ2 should be performed separately from γ1. The specific operations are as follows:

[0487]

[0488] Where Ψ1 = G i x p Ψ2=G i x represents the current multipath component calculated based on the estimated time delay-Doppler parameters in each iteration.

[0489] Module M5: Eliminates interference between communication data and pilot symbols at the receiving end, while performing channel estimation and data detection.

[0490] The M5 module model includes:

[0491] Module M5.1: Calculates the estimated channel gain using the estimated time delay and Doppler parameters;

[0492] Specifically, module M5.1 includes:

[0493] Based on the relationship between the pilot signal and the original time-delay-Doppler domain channel:

[0494]

[0495] Where y p The received signal is the time-delay-Doppler domain signal after the pilot symbols have traveled through the channel. L=(l max +1)(2k max +1), where each column is Ψ1 obtained from the outer loop mentioned above. Its elements are the channel gain of each path;

[0496] Construct matrix B = [G1x] based on the pilot signals and the estimated time-delay-Doppler domain parameters. p G2x p , ..., G P X p Because the pilot signal is superimposed on the data symbol, the receiver can only obtain y instead of y. p Therefore, we first roughly estimate the channel gain:

[0497]

[0498] Module M5.2: Eliminates interference from superimposed pilot signals on data symbols and detects data symbols using a time-delay-Doppler domain maximum ratio combining algorithm;

[0499] Specifically, module M5.2 includes:

[0500] The time-delay-Doppler domain equivalent channel matrix is ​​calculated based on the channel gain, and the influence of the pilot is eliminated from the received signal y, i.e.:

[0501]

[0502] right Symbol detection is performed using the Maximum Ratio Combining (MRC) algorithm to obtain estimates of the time-delay-Doppler domain data symbols.

[0503] Module M5.3: Eliminates interference from data symbols to superimposed pilots, re-estimates channel gain, and iteratively completes channel estimation and data detection together with module M5.2;

[0504] Specifically, module M5.3 includes:

[0505] Based on the estimation of data symbols Eliminate the influence of data from the received signal y, that is:

[0506]

[0507] by The update step estimates the sample points used for channel gain estimation. Modules M5.1 and M5.2 are run again and repeated until certain termination conditions are met (e.g., the iteration has reached the maximum set number of rounds, or the change in the estimation result of this round compared to the previous round is less than a set threshold, in which case the iterative algorithm can be considered to have converged). The loop is then exited, and the channel estimation and data demodulation results are finally obtained.

[0508] This invention provides a system for constructing a sensing-assisted uplink channel estimation based on orthogonal time-frequency spatial control. Compared to systems that only consider integer Doppler, which suffer from drastic performance degradation in fractional Doppler cases, this system is more suitable for practical scenarios. Compared to channel estimation using only pilots, it can estimate fractional Doppler parameters more accurately, thereby improving communication performance. Compared to other orthogonal time-frequency spatial channel estimation methods, it can further reduce the number of required sampling points and lower computational complexity while ensuring the accuracy of channel estimation (fractional Doppler case). The system includes a novel channel estimation scheme based on block superimposed pilots, which can further reduce the number of required channel sampling points and lower algorithm complexity compared to schemes based on embedded pilots and fully superimposed pilots. A modified compressed sensing recovery algorithm is proposed, which can accurately estimate the fractional Doppler channel without constructing a fractional dictionary matrix, compared to the orthogonal matching pursuit (OMP) algorithm.

[0509] Those skilled in the art will understand that, besides implementing the system and its various devices, modules, and units provided by this invention in the form of purely computer-readable program code, the same functions can be achieved entirely through logical programming of the method steps, making the system and its various devices, modules, and units of this invention function in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers. Therefore, the system and its various devices, modules, and units provided by this invention can be considered as a hardware component, and the devices, modules, and units included therein for implementing various functions can also be considered as structures within the hardware component; alternatively, the devices, modules, and units for implementing various functions can be considered as both software modules implementing the method and structures within the hardware component.

[0510] Specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art can make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. Unless otherwise specified, the embodiments and features described in this application can be arbitrarily combined with each other.

Claims

1. A sensing-assisted uplink channel estimation method based on orthogonal time-frequency conditioning, characterized in that, include: Step S1: Generate pilot symbols in the time-delay Doppler domain and superimpose them with communication data symbols to form a transmission frame; Step S2: Convert the time-delay Doppler domain transmission frame into a time-domain uplink signal, transmit it through the transmitting end user, and after passing through the wireless channel, convert it back into a time-delay Doppler domain reception signal at the receiving end base station; Step S3: Instruct the base station to collect sensing echoes and convert the backscattered signals formed by the transmission or diffraction of the recently transmitted downlink signals by users and potential targets into the time-delay Doppler domain; Step S4: At the receiving end, time delay and Doppler parameters are estimated using uplink pilot and sensing echo; Step S5: Using the estimated time delay and Doppler parameters, eliminate the interference between communication data and pilot symbols at the receiving end, and simultaneously perform channel estimation and data detection. In step S4: Step S4.1: At the receiving end, extract some sampling points from the received signal in the time-delay Doppler domain, construct the sensing matrix and the vector to be reconstructed based on the known uplink pilot, and estimate the integer time-delay Doppler parameters; Step S4.2: Utilize the sensing echo generated by the downlink signal The fractional Doppler estimate is obtained by dividing the interval into regions within the neighborhood of the integer Doppler parameters and iteratively searching. In step S5: Step S5.1: Calculate the estimated channel gain using the estimated time delay and Doppler parameters; Step S5.2: Eliminate the interference of superimposed pilot signals on data symbols by detecting data symbols using the time-delay Doppler domain maximum ratio combining algorithm; Step S5.3: Eliminate the interference of data symbols on the superimposed pilots, re-estimate the channel gain, and iterate together with step S5.2 to complete the channel estimation and data detection; In step S1: Measure the maximum delay spread and maximum Doppler spread of the channel, and determine the relationship between channel spread and delay-Doppler domain index: in, For the delay spread of a certain path, For Doppler extension, For the path index, For the delay axis index corresponding to the delay extension, The Doppler axis index corresponds to the Doppler extension; M is the number of time-delay blocks in the time-delay Doppler domain planar mesh, and N is the number of Doppler blocks in the time-delay Doppler domain planar mesh. Let T be the subcarrier frequency interval and T be the symbol duration; calculate the maximum delay index in the delay-Doppler domain. And the maximum Doppler index is The total number of randomized generators is Pilot symbols; Selected range ,in , The index of the Doppler axis corresponding to the maximum Doppler extension. The delay axis index corresponding to the maximum delay extension; The pilot symbols are superimposed one by one onto the time-delay Doppler domain data symbols within this range. superior: in Communication data symbols in matrix form. The pilot symbols are in matrix form.

2. The sensing-assisted uplink channel estimation method based on orthogonal time-frequency regulation according to claim 1, characterized in that: In step S2: The time-delay Doppler domain symbols are converted into time-frequency domain signals by inverse discrete symmetric Fourier transform: in, Sending signals in the time-frequency domain, It is a time-delayed Doppler field symbol elements, e is the base of the natural logarithm, and j is the imaginary unit. The Heisenberg transform is used to transform the time-frequency domain symbols into baseband time-domain signals. : in, The transmitted pulse waveform is represented by a rectangular transmit and receive waveform, with a cyclic prefix inserted in the time domain to form the final transmitted signal; This indicates that the independent variable of the function is time; Represented in matrix form: ； in, This is the conjugate transpose operation of a matrix; Transmit signals in matrix form for the time-delay-Doppler domain; and To obtain the normalized DFT matrix, vectorize S to get... : in, , For column vectorization operations, It is the Kronecker product. To represent a complex number, It is the size of The identity matrix; Because the channel exhibits sparsity in the time-delay Doppler domain, the complex baseband channel impulse response Represented as: in, P This represents the number of multipath components, and also the number of channel taps in the delay-Doppler domain. Indicates the first i The complex channel gain of each path; Indicates the first i The delay of the path, Indicates the first i Doppler frequency shift along the path; Let be the impulse function. For time delay, For Doppler frequency shift; Delay Doppler domain channel taps and , The relationship is: in, and They respectively represent the corresponding number i Integer delay tap and Doppler tap indices for each path, fractional Doppler. Represents the offset from the nearest integer tap, the size of which satisfies Meanwhile, the relationship between the maximum channel delay spread and maximum Doppler spread and the delay-Doppler domain index is obtained as follows: in, This represents the maximum delay spread of the channel. For maximum Doppler extension, The delay axis index for the delay-Doppler domain corresponding to the maximum delay spread. The time-delay Doppler domain Doppler axis index corresponding to the maximum Doppler extension; Signal Transmitting and receiving signals in a time-varying channel It is given by the following formula: in It is zero-mean additive white Gaussian noise with variance of ; Will Expressed in vector form as : in, , This is a forward cyclic shift matrix used to characterize the delay. It is a diagonal matrix. , Used to characterize Doppler frequency shift ; At the receiving end, the cyclic prefix is ​​first removed in the time domain, and then the signal is transformed to the time-frequency domain and the time-delay Doppler domain successively through Wigner transform and discrete symmetric Fourier transform. The above process can be represented by a matrix as follows: in, and The matrix forms of the received signals in the time-frequency domain and the time-delay Doppler domain are respectively, where, For the time-delay domain received signal matrix; Vectorization yields: in, denoted as the time-delay Doppler domain equivalent channel matrix, ; Step S3 includes: The same operation as in step S2 is performed on the sensing echo generated by the downlink signal, converting it to the time-delay Doppler domain to obtain... .

3. The sensing-assisted uplink channel estimation method based on orthogonal time-frequency regulation according to claim 2, characterized in that: Step S4.1 includes: For the received signal Extract sampling points within a given range, i.e. , forming a measurement vector ; According to the pilot matrix Constructing a matrix , Each column , elements , and These are cyclic shift operations modulo N and M, respectively, where the elements of the pilot matrix are: in, The power of the pilot symbol; Get the initial Then, also according to the scope Extract The corresponding row, the range is one If we take a 0-1 matrix and vectorize its columns, then the row index of the 1 is the index of the element to be extracted. The row index, after being updated, results in a smaller value. ; Constructing a perception matrix : in, It is the phase offset matrix. It represents the Hadamardi (or Hadama) stack; Searching for the column in A that best matches the current residual yields an integer time-delay Doppler index for a path, namely: in For each column of A, the residual The initial value is ; Step S4.2 includes: Estimating Doppler frequency shift : in, , , It is the integer index obtained in step S4.1 residual The initial value is the time delay of the downlink signal x and the Doppler domain sensing echo. .

4. The sensing-assisted uplink channel estimation method based on orthogonal time-frequency regulation according to claim 3, characterized in that: Step S5.1 includes: Based on the relationship between the pilot signal and the original time-delay Doppler domain channel: in, The received signal is the Doppler domain signal with time delay after the pilot symbols have passed through the channel. , , Its elements are the channel gain of each path; Construct a matrix based on the pilot signals and the estimated time-delay Doppler domain parameters. Because the pilot signal is superimposed on the data symbol, the receiver receives y instead of... Therefore, a coarse estimate of the channel gain is first obtained: in The channel estimation results are in vector form. For matrix The false reversal; Step S5.2 includes: The equivalent channel matrix in the Doppler domain of the time delay is calculated based on the channel gain, and the influence of the pilot is eliminated from the received signal y, i.e.: To eliminate the influence of pilot signals, the received signal more closely approximates the channel's response to data symbols. Symbol detection is performed to obtain an estimate of the symbols in the time-delay Doppler domain data. ; Step S5.3 includes: Based on the estimation of data symbols To eliminate the influence of data from the received signal y, that is: To eliminate the influence of data, the received signal more closely approximates the channel's response to the pilot symbols. Update the sample points used to estimate the channel gain in the update step, repeat steps S5.1 and S5.2, and repeat the operation until the preset termination condition is met, exit the loop, and finally obtain the channel estimation and data demodulation results.

5. A sensing-assisted uplink channel estimation system based on orthogonal time-frequency air conditioning, characterized in that, include: Module M1: Generates pilot symbols in the time-delay Doppler domain, which are superimposed with communication data symbols to form a transmission frame; Module M2: Converts the time-delay Doppler domain transmission frame into a time-domain uplink signal, which is transmitted by the user at the transmitting end, passes through the wireless channel, and is then converted back into a time-delay Doppler domain reception signal at the receiving end base station; Module M3: Enables the base station to collect sensing echoes and convert the backscattered signals formed by the transmission or diffraction of the recently transmitted downlink signals by users and potential targets into the time-delay Doppler domain; Module M4: At the receiving end, time delay and Doppler parameters are estimated using uplink pilot and sensing echo; Module M5: Using the estimated time delay and Doppler parameters, it eliminates the interference between communication data and pilot symbols at the receiving end, while performing channel estimation and data detection. In module M4: Module M4.1: At the receiving end, extract some sampling points from the received signal in the time-delay Doppler domain, construct a sensing matrix and a vector to be reconstructed based on the known uplink pilot, and estimate the integer time-delay Doppler parameters; Module M4.2: Sensing echo generated from downlink signals The fractional Doppler estimate is obtained by dividing the interval into regions within the neighborhood of the integer Doppler parameters and iteratively searching. In module M5: Module M5.1: Calculates the estimated channel gain using the estimated time delay and Doppler parameters; Module M5.2: Eliminates interference from superimposed pilot signals on data symbols and detects data symbols using a time-delay Doppler domain maximum ratio combining algorithm; Module M5.3: Eliminates interference from data symbols to superimposed pilots, re-estimates channel gain, and iteratively completes channel estimation and data detection together with module M5.2; In module M1: Measure the maximum delay spread and maximum Doppler spread of the channel, and determine the relationship between channel spread and delay-Doppler domain index: in, For the delay spread of a certain path, For Doppler extension, For the path index, For the delay axis index corresponding to the delay extension, The Doppler axis index corresponds to the Doppler extension; M is the number of time-delay blocks in the time-delay Doppler domain planar mesh, and N is the number of Doppler blocks in the time-delay Doppler domain planar mesh. Let T be the subcarrier frequency interval and T be the symbol duration; calculate the maximum delay index in the delay-Doppler domain. And the maximum Doppler index is The total number of randomized generators is Pilot symbols; Selected range ,in , The index of the Doppler axis corresponding to the maximum Doppler extension. The delay axis index corresponding to the maximum delay extension; The pilot symbols are superimposed one by one onto the time-delay Doppler domain data symbols within this range. superior: in Communication data symbols in matrix form. The pilot symbols are in matrix form.

6. The sensing-assisted uplink channel estimation system based on orthogonal time-frequency regulation according to claim 5, characterized in that: In module M2: The time-delay Doppler domain symbols are converted into time-frequency domain signals by inverse discrete symmetric Fourier transform: in, Sending signals in the time-frequency domain, It is a time-delayed Doppler field symbol elements, e is the base of the natural logarithm, and j is the imaginary unit. The Heisenberg transform is used to transform the time-frequency domain symbols into baseband time-domain signals. : in, The transmitted pulse waveform is represented by a rectangular transmit and receive waveform, with a cyclic prefix inserted in the time domain to form the final transmitted signal; This indicates that the independent variable of the function is time; Represented in matrix form: ； in, This is the conjugate transpose operation of a matrix; Transmit signals in matrix form for the time-delay-Doppler domain; and To obtain the normalized DFT matrix, vectorize S to get... : in, , For column vectorization operations, It is the Kronecker product. To represent a complex number, It is the size of The identity matrix; Because the channel exhibits sparsity in the time-delay Doppler domain, the complex baseband channel impulse response Represented as: in, P This represents the number of multipath components, and also the number of channel taps in the delay-Doppler domain. Indicates the first i The complex channel gain of each path; Indicates the first i The delay of the path, Indicates the first i Doppler frequency shift along the path; Let be the impulse function. For time delay, For Doppler frequency shift; Delay Doppler domain channel taps and , The relationship is: in, and They respectively represent the corresponding number i Integer delay tap and Doppler tap indices for each path, fractional Doppler. Represents the offset from the nearest integer tap, the size of which satisfies Meanwhile, the relationship between the maximum channel delay spread and maximum Doppler spread and the delay-Doppler domain index is obtained as follows: in, This represents the maximum delay spread of the channel. For maximum Doppler extension, The delay axis index for the delay-Doppler domain corresponding to the maximum delay spread. The time-delay Doppler domain Doppler axis index corresponding to the maximum Doppler extension; Signal Transmitting and receiving signals in a time-varying channel It is given by the following formula: in It is zero-mean additive white Gaussian noise with variance of ; Will Expressed in vector form as : in, , This is a forward cyclic shift matrix used to characterize the delay. It is a diagonal matrix. , Used to characterize Doppler frequency shift ; At the receiving end, the cyclic prefix is ​​first removed in the time domain, and then the signal is transformed to the time-frequency domain and the time-delay Doppler domain successively through Wigner transform and discrete symmetric Fourier transform. The above process can be represented by a matrix as follows: in, and The matrix forms of the received signals in the time-frequency domain and the time-delay Doppler domain are respectively, where, For the time-delay domain received signal matrix; Vectorization yields: in, denoted as the time-delay Doppler domain equivalent channel matrix, ; The module M3 includes: The same operation as module M2 is performed on the sensing echo generated by the downlink signal, converting it to the time-delay Doppler domain to obtain... .

7. The sensing-assisted uplink channel estimation system based on orthogonal time-frequency regulation according to claim 5, characterized in that: The module M4.1 includes: For the received signal Extract sampling points within a given range, i.e. , forming a measurement vector ; According to the pilot matrix Constructing a matrix , Each column , elements , and These are cyclic shift operations modulo N and M, respectively, where the elements of the pilot matrix are: in, The power of the pilot symbol; Get the initial Then, also according to the scope Extract The corresponding row, the range is one If we take a 0-1 matrix and vectorize its columns, then the row index of the 1 is the index of the element to be extracted. The row index, after being updated, results in a smaller value. ; Constructing a perception matrix : in, It is the phase offset matrix. It represents the Hadamardi (or Hadama) stack; Searching for the column in A that best matches the current residual yields an integer time-delay Doppler index for a path, namely: in For each column of A, the residual The initial value is ; The module M4.2 includes: Estimating Doppler frequency shift : in, , , It is the integer index obtained from module M4.1 residual The initial value is the time delay of the downlink signal x and the Doppler domain sensing echo. ; The module M5.1 includes: Based on the relationship between the pilot signal and the original time-delay Doppler domain channel: in, The received signal is the Doppler domain signal with time delay after the pilot symbols have passed through the channel. , , Its elements are the channel gain of each path; Construct a matrix based on the pilot signals and the estimated time-delay Doppler domain parameters. Because the pilot signal is superimposed on the data symbol, the receiver receives y instead of... Therefore, a coarse estimate of the channel gain is first obtained: in The channel estimation results are in vector form. For matrix The false reversal; The module M5.2 includes: The equivalent channel matrix in the Doppler domain of the time delay is calculated based on the channel gain, and the influence of the pilot is eliminated from the received signal y, i.e.: To eliminate the influence of pilot signals, the received signal more closely approximates the channel's response to data symbols. Symbol detection is performed to obtain an estimate of the symbols in the time-delay Doppler domain data. ; The module M5.3 includes: Based on the estimation of data symbols To eliminate the influence of data from the received signal y, that is: To eliminate the influence of data, the received signal more closely approximates the channel's response to the pilot symbols. The sample points used to estimate the channel gain are updated, and modules M5.1 and S5.2 are repeated until the preset termination condition is met, then the loop is exited, and finally the channel estimation and data demodulation results are obtained.

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