A channel estimation method for OTFS system based on roundabout matching pursuit

Abstract

The invention belongs to the technical field of wireless communication, and in particular relates to an OTFS system channel estimation method based on roundabout matching pursuit; the method comprises: constructing a signal to be sent at a transmitting end of the OTFS system, comprising placing a pilot symbol and a data symbol in a delay-Doppler domain; converting the signal to be sent from the delay-Doppler domain to a time domain at the transmitting end to obtain a time domain signal; sending the time domain signal to a receiving end; the receiving end receives the time domain signal and converts the time domain signal from the time domain to the delay-Doppler domain; performing channel estimation using a DMP-TD algorithm in the delay-Doppler domain to obtain a channel estimation result of the OTFS system; compared with a traditional OMP channel estimation algorithm, the channel estimation method of the invention has better channel estimation performance.

Description

Technical Field

[0001] The present invention belongs to the technical field of wireless communications, and in particular relates to an OTFS system channel estimation method based on roundabout matching pursuit. Background Art

[0002] At present, with the massive development of high-speed railways and highways, the traditional Orthogonal Frequency Division Multiplexing (OFDM) modulation technology can no longer meet the communication needs of these scenarios. In this high-speed mobile scenario, the wireless channel exhibits dual dispersion, and the multipath propagation effect will cause time dispersion, although Doppler shift will cause frequency dispersion. Orthogonal frequency division multiplexing technology (OFDM) has strong data transmission capabilities and good anti-interference performance against inter-symbol interference (ISI) caused by channel multipath effects. However, in high-speed mobile scenarios, such as high-speed railway communications, drone communications, and vehicle networking communications, the relatively high-speed movement between the transmitter and receiver produces a large Doppler frequency offset, which destroys the orthogonality between the carriers and causes inter-carrier interference (ICI), which seriously damages the performance of the OFDM system.

[0003] Orthogonal Time Frequency Space (OTFS) modulation technology is a new communication technology proposed in recent years. It has more advantages than traditional OFDM technology in high-speed mobile scenarios. OTFS converts the signal from the time domain to the delay-Doppler (DD) domain through a series of transformations, and performs channel estimation, signal detection and other operations in this domain. Since the channel in the DD domain is stable, each symbol in the OTFS symbol enjoys almost the same channel gain. In addition, due to the sparse characteristics of the DD domain channel, the channel estimation problem can be converted into a sparse signal reconstruction problem when performing channel estimation in the DD domain.

[0004] Rasheed OK et al. proposed a channel estimation method based on compressed sensing in their paper “Sparse Delay Doppler Channel Estimation in Rapidly Time-Varying Channels for Multiuser OTFS on the Uplink”. This method uses the orthogonal matching pursuit (OMP) algorithm to implement channel estimation in the DD domain. Although the performance is improved compared with the pulse-based channel estimation method, its channel estimation accuracy still needs to be improved.

[0005] In summary, there is an urgent need for an OTFS system channel estimation method to solve the problem of insufficient accuracy of OTFS system channel estimation. Summary of the invention

[0006] In view of the shortcomings of the prior art, the present invention proposes an OTFS system channel estimation method based on circuitous matching pursuit, the method comprising:

[0007] S1: construct the signal to be sent at the transmitter of the OTFS system, including placing pilot symbols and data symbols in the delay-Doppler domain;

[0008] S2: at the transmitting end, convert the signal to be transmitted from the delay-Doppler domain to the time domain to obtain a time domain signal; and send the time domain signal to the receiving end;

[0009] S3: The receiving end receives the time domain signal and converts the time domain signal from the time domain to the delay-Doppler domain;

[0010] S4: Use the DMP-TD algorithm to perform channel estimation in the delay-Doppler domain to obtain the channel estimation result of the OTFS system.

[0011] Preferably, the manner of placing data symbols in the delay-Doppler domain is expressed as:

[0012]

[0013] Where x[k,l] represents the kth data symbol on the lth subcarrier in the OTFS system data block, x p represents the inserted pilot symbol, l p Indicates the index of the pilot on the delay axis, k p Indicates the index of the pilot on the Doppler axis, k max represents the maximum Doppler shift, l max Indicates the maximum delay, x d Represents the data symbol for placement.

[0014] Preferably, the process of converting the signal to be transmitted from the delay Doppler domain to the time domain includes: performing an ISFFT inverse sigmoid Fourier transform on the OTFS data symbols to convert them to the time-frequency domain to obtain a time-frequency domain signal; and performing a Heisenberg transform on the time-frequency domain signal to convert it to the time domain to obtain a time domain signal.

[0015] Preferably, the process of converting the time domain signal from the time domain to the delay-Doppler domain includes: performing a Wigner transform on the time domain signal to convert it to the time-frequency domain to obtain a time-frequency domain signal; performing a sigma Fourier transform on the time-frequency domain signal to convert it to the delay-Doppler domain to obtain a delay-Doppler domain signal.

[0016] Preferably, the process of using the DMP-TD algorithm to perform channel estimation includes:

[0017] S41: Initialize the estimated parameters, including the dynamic threshold γ 1 , decision threshold γ 2 , the channel multipath number K and the number of reduced elements b;

[0018] S42: Calculate the residual error and obtain the support set S;

[0019] S43: Let b=b+1, and determine whether b<K is satisfied. If so, execute step S44; if not, execute step S47;

[0020] S44: sequentially reduce and expand the support set to obtain a sub-inner product matrix and a coefficient matrix;

[0021] S45: Determine whether the residual error is less than the dynamic threshold γ 1 If satisfied, execute step S47; if not satisfied, execute step S46;

[0022] S46: Determine whether the error update condition is met. If so, update the residual error, the sub-inner product matrix and the coefficient matrix, and calculate the reconstructed signal according to the coefficient matrix; otherwise, set b=0 and return to step S43;

[0023] S47: Determine whether the support set S satisfies Y DD (S i )≥γ 2 , if satisfied, then output the support set S and the reconstructed signal x; if not satisfied, then update the dynamic threshold γ 1 At the same time, let b = 0 and return to step S43; wherein Y DD represents the matrix form of the received data in the delay-Doppler domain, Y DD (S i ) represents the Sth in the delay-Doppler domain i The value of the received data.

[0024] Furthermore, the decision threshold is initialized to γ 2 =3σ,σ 2 Represents the average noise power.

[0025] Furthermore, the error update condition is:

[0026]

[0027] in, Removing element ω from the support set S 1 ,…,ω b Then the element v b ,…,ν1 Add to the support set S, Δ S Represents the residual error.

[0028] Furthermore, the formula for updating the dynamic threshold is:

[0029]

[0030] Among them, γ 1 ′ represents the updated dynamic threshold, γ 1 Indicates the dynamic threshold before updating.

[0031] The beneficial effects of the present invention are as follows: the present invention utilizes the high reconstruction accuracy advantage of the detouring matching pursuit (DMP) algorithm, combined with the threshold decision (Threshold decision) idea, and proposes a detouring matching pursuit-threshold decision (DMP-TD) channel estimation method. When the sparse characteristics of the delay-Doppler domain channel are not obvious enough, that is, when the number of channels is large, the accuracy of the reconstructed signal x will decrease; the present invention adopts a combination of dynamic threshold and threshold decision to perform channel estimation, reducing the algorithm's tolerance to errors γ 1 , to ensure the accuracy of the reconstructed signal; the simulation results show that compared with the traditional OMP channel estimation algorithm, the channel estimation method of the present invention has better channel estimation performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 It is a flow chart of the OTFS system channel estimation method based on circuitous matching pursuit in the present invention;

[0033] Figure 2 It is a schematic diagram of time domain-Doppler domain modulation of the OTFS system in the present invention;

[0034] Figure 3 A comparison chart of channel estimation simulation results of the OTFS system of the present invention and the comparative method under the conditions of a speed of 75 m / s and a multipath number of 10;

[0035] Figure 4 It is a comparison chart of channel estimation simulation results of the OTFS system of the present invention and the comparative method under the conditions of a speed of 150m / s and a multipath number of 10. DETAILED DESCRIPTION

[0036] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0037] The present invention proposes a channel estimation method for an OTFS system based on circuitous matching pursuit. Figure 1 As shown, the method comprises the following steps:

[0038] S1: Construct the signal to be sent at the transmitter of the OTFS system, including placing pilot symbols and data symbols in the delay-Doppler domain.

[0039] The way to place data symbols in the delay-Doppler domain is expressed as:

[0040]

[0041] Wherein, x[k,l] represents the kth data symbol on the lth subcarrier in the OTFS system data block, k={0,1,2,...,N-1}, l={0,1,2,...M-1}, M and N represent the total number of subcarriers and the total number of data symbols on the subcarriers of the transmitting end OTFS system respectively; p represents the inserted pilot symbol, l p Indicates the index of the pilot on the delay axis, k p Indicates the index of the pilot on the Doppler axis, k max represents the maximum Doppler shift, l max Indicates the maximum delay, x d Represents the data symbol for placement.

[0042] S2: At the transmitting end, the signal to be transmitted is converted from the delay Doppler domain to the time domain to obtain a time domain signal; and the time domain signal is sent to the receiving end.

[0043] like Figure 2 As shown, the process of converting the signal to be transmitted from the delay Doppler domain to the time domain includes: performing ISFFT inverse sigmoid Fourier transform on the OTFS data symbol to convert it to the time-frequency domain to obtain a time-frequency domain signal; performing Heisenberg transform on the time-frequency domain signal to convert it to the time domain to obtain a time domain signal.

[0044] S3: The receiving end receives the time domain signal and converts the time domain signal from the time domain to the delay-Doppler domain.

[0045] The process of converting the time domain signal from the time domain to the delay-Doppler domain includes: performing Wigner transform on the time domain signal to convert it to the time-frequency domain to obtain a time-frequency domain signal; performing sigma Fourier transform on the time-frequency domain signal to convert it to the delay-Doppler domain to obtain a delay-Doppler domain signal.

[0046] S4: Use the DMP-TD algorithm to perform channel estimation in the delay-Doppler domain to obtain the channel estimation results of the OTFS system, including the channel gain, delay and Doppler shift value of each multipath.

[0047] The process of channel estimation using the DMP-TD algorithm in the delay-Doppler domain includes:

[0048] S41: Initialize the estimated parameters, including the dynamic threshold γ 1 , decision threshold γ 2 , the channel multipath number K and the number of reduced elements b; first, initialize the decision threshold γ 2 =3σ, the channel multipath number K is determined according to the actual situation, the number of reduced elements b = 0, the dynamic threshold γ 1 =10 -3 ; Among them, σ 2 Represents the average noise power.

[0049] S42: Calculate the residual error and obtain the support set S.

[0050] Calculate the residual error:

[0051]

[0052] Φ s =Φ(Λ,S)

[0053]

[0054] Among them, r s represents the residual, y represents the delay-Doppler domain received signal Y DD The vector form of Φ s represents the intermediate parameter matrix, Δ s represents the residual error, Φ represents the perception matrix, Λ represents the full set of matrices, that is, the set of all row numbers or column numbers of the matrix, S represents the support set, and the support set is initially empty.

[0055] The process of obtaining the support set S includes:

[0056] calculate Δ [S,i] represents the residual error of the new support set after putting element i into the support set S; update the support set S = S′∪{i}, S′ is the support set calculated last time, and S is the updated support set; Select The corresponding atom Φ i Add to Φ s , repeat this step K times to get the support set S; support set S = [s 1 ,s 2 ,...,s k ] T ,S∈K×1, contains the position index of each multipath in the delay-Doppler domain grid. Among them:

[0057]

[0058] Common factor: f s (i)=Ψ(i,i)-Ψ(i,S)C S (Λ,L S (i)); Positioning function: L S (i), i∈S, represents the position of i in the set S; Ψ represents the sensor matrix, which is the input of the algorithm, Ψ=B T B, B = [Φ, y]; end indicates the last element (row or column) of the vector (matrix). represents the complement of the support set S; the complement of S / {i} is That is, S / {i} means removing element i from the set S.

[0059] S43: Let b=b+1, and determine whether b<K is satisfied. If so, execute step S44; if not, execute step S47.

[0060] S44: The support set is reduced and expanded in turn to obtain a sub-inner product matrix and a coefficient matrix.

[0061] Reduce the support set:

[0062] Delete ω from the support set S b , and calculate the deleted element ω in the support set S 1 ,…,ω b The inverse inner product matrix of and the coefficient matrix Let t=b.

[0063] in, Removing element ω from the support set S 1 ,…,ω b .

[0064] Augmented support set:

[0065] Select ν tAdd the support set S and judge {ω b ,…,ω t}∪{v b ,…,v t} and {ω b ,…,ω t} are the same, if not, set t = t-1 and recalculate the support set S to delete the element ω 1 ,…,ω b And the element ν b ,…,ν 1 Add to the sub-inner product matrix under the support set S and the coefficient matrix Repeat the process of expanding the support set until t=0; if they are the same, return to step S43.

[0066] S45: Determine whether the residual error is less than the dynamic threshold γ 1 If satisfied, execute step S47; if not satisfied, execute step S46.

[0067] S46: Determine whether the error update condition is met. If so, update the residual error, the sub-inner product matrix and the coefficient matrix, and calculate the reconstructed signal based on the sub-inner product matrix and the coefficient matrix; otherwise, set b=0 and return to step S43.

[0068] Determine whether the error update condition is met: Removing element ω from the support set S 1 ,…,ω b Then add the element ν b ,…,ν 1 Add to the support set S; if satisfied, update the support set S = [S / {ω 1 ,…,ω b},ν b ,…,ν 1 ] and recalculate the sub-inner product matrix and the coefficient matrix The reconstructed signal x is obtained according to the coefficient matrix, and b=0 is set; if not satisfied, return to step S43.

[0069] S47: Determine whether the support set S satisfies Y DD (S i )≥γ 2 ,j={1,2,..,K}, if satisfied, then output the support set S and the reconstructed signal x; if not satisfied, then update the dynamic threshold γ 1 At the same time, let b = 0 and return to step S43; wherein S i represents the i-th element of the support set S, Y DD represents the matrix form of the received data in the delay-Doppler domain, YDD (S i ) represents the delay-Doppler domain S i The value of the received data.

[0070] Preferably, the formula for updating the dynamic threshold is:

[0071]

[0072] Among them, γ 1 ′ represents the updated dynamic threshold, γ 1 Indicates the dynamic threshold before updating.

[0073] Output reconstructed signal x = [x 1 ,x 2 ,...,x MN ] T ,x∈MN×1, represents the channel gain value corresponding to each resource grid on the delay-Doppler resource grid. If x i ≠0, i∈[1,MN], it means that there is an actual channel path, otherwise there is no actual channel path. According to the index value of each multipath in the delay-Doppler domain grid, the delay value and Doppler frequency shift value of each multipath can be calculated.

[0074] Evaluation of the present invention:

[0075] The simulation parameters are set as follows: center frequency 2.15 GHz; subcarrier spacing 15 KHz, total number of subcarriers M is 512, number of carrier symbols N is 64, modulation mode is QPSK, channel multipath number is 10, and channel model is TDL-C channel.

[0076] The NMSE indicator is used for evaluation:

[0077]

[0078] Among them, NMSE represents the normalized mean square error of channel estimation, represents the estimated channel coefficient, h represents the actual channel coefficient, ||·|| 2 It means to find the square of the absolute value.

[0079] like Figure 3 , Figure 4As shown, the horizontal axis represents the signal-to-noise ratio of the transmitted symbol, in dB; the vertical axis represents the normalized mean square error of the channel estimation; the square indicates the channel estimation scheme based on the pulse pilot, the diamond indicates the channel estimation scheme using the OMP algorithm, and the circle indicates the channel estimation scheme using the DMP-TD algorithm. It can be seen that when the moving speed is 75m / s or 150m / s, the normalized mean square error of the channel estimation scheme using the OMP algorithm is smaller than that of the channel estimation scheme based on the pulse pilot, and the normalized mean square error of the DMP-TD algorithm of the present invention is smaller than both. It can be seen that the DMP-TD algorithm channel estimation scheme of the present invention has a more superior channel estimation performance and has a higher channel estimation accuracy than the OMP algorithm.

[0080] The above embodiments further illustrate the purpose, technical solutions and advantages of the present invention in detail. It should be understood that the above embodiments are only preferred implementation modes of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made to the present invention within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A channel estimation method for an OTFS system based on circuitous matching pursuit, characterized in that: Including: S1: Construct the signal to be transmitted at the transmitter end of the OTFS system, including placing pilot symbols and data symbols in the delay-Doppler domain; S2: At the transmitter end, convert the signal to be transmitted from the delay-Doppler domain to the time domain to obtain a time-domain signal; send the time-domain signal to the receiver end; S3: The receiver end receives the time-domain signal and converts the time-domain signal from the time domain to the delay-Doppler domain; S4: Perform channel estimation using the DMP-TD algorithm in the delay-Doppler domain to obtain the channel estimation result of the OTFS system; The process of performing channel estimation using the DMP-TD algorithm includes: S41: Initialize the estimation parameters, including the dynamic threshold γ1, the decision threshold γ2, the number of channel multipaths K, and the number of reduced elements b; S42: Calculate the residual error and obtain the support set S; S43: Let b = b + 1, and judge whether b < K is satisfied. If satisfied, execute step S44; if not satisfied, execute step S47; S44: Perform support set reduction and augmentation processing in sequence to obtain a sub-inner product matrix and a coefficient matrix; S45: Judge whether the residual error is less than the dynamic threshold γ1. If satisfied, execute step S47; if not satisfied, execute step S46; S46: Judge whether the error update condition is satisfied. If satisfied, update the residual error, the sub-inner product matrix, and the coefficient matrix, and calculate the reconstructed signal according to the coefficient matrix; otherwise, let b = 0 and return to step S43; S47: Determine whether the support set S satisfies Y DD (S i )≥γ2, if it is satisfied, then output the support set S and the reconstructed signal x; if it is not satisfied, then update the dynamic threshold γ1 and set b=0, and return to step S43; where Y DD represents the matrix form of the received data in the delay-Doppler domain, Y DD (S i ) represents the Sth in the delay-Doppler domain i The value of the received data.

2. The OTFS system channel estimation method based on circuitous matching pursuit according to claim 1, characterized in that: The way of placing data symbols in the delay-Doppler domain is expressed as: Where x[k,l] represents the kth data symbol on the lth subcarrier in the OTFS system data block, x p represents the inserted pilot symbol, l p Indicates the index of the pilot on the delay axis, k p Indicates the index of the pilot on the Doppler axis, k max represents the maximum Doppler shift, l max Indicates the maximum delay, x d Represents the data symbol for placement.

3. The OTFS system channel estimation method based on circuitous matching pursuit according to claim 1, characterized in that: The process of converting the signal to be transmitted from the delay-Doppler domain to the time domain includes: performing an inverse symplectic Fourier transform (ISFFT) on the OTFS data symbols to convert them to the time-frequency domain to obtain a time-frequency domain signal; performing a Heisenberg transform on the time-frequency domain signal to convert it to the time domain to obtain a time-domain signal.

4. The OTFS system channel estimation method based on circuitous matching pursuit according to claim 1, characterized in that: The process of converting the time-domain signal from the time domain to the delay-Doppler domain includes: performing a Wigner transform on the time-domain signal to convert it to the time-frequency domain to obtain a time-frequency domain signal; performing a symplectic Fourier transform on the time-frequency domain signal to convert it to the delay-Doppler domain to obtain a delay-Doppler domain signal.

5. The OTFS system channel estimation method based on circuitous matching pursuit according to claim 1, characterized in that: The decision threshold is initialized to γ2=3σ, σ 2 Represents the average noise power.

6. The OTFS system channel estimation method based on circuitous matching pursuit according to claim 1, characterized in that: The said error update condition is: in, Removing elements ω1,…,ω from the support set S b Then the element ν b ,…,ν1 is added to the support set S, Δ S Represents the residual error.

7. The OTFS system channel estimation method based on circuitous matching pursuit according to claim 1, characterized in that: The formula for updating the dynamic threshold is: where γ1′ represents the updated dynamic threshold, and γ1 represents the dynamic threshold before update.

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