Detection method and system of MIMO-OCDM detector based on wide linear minimum mean square error

Abstract

The invention discloses a wide linear minimum mean square error-based MIMO-OCDM detector detection method and system, and the method comprises the steps: demodulating a signal received by a receiving antenna based on discrete Fresnel change, and obtaining an observation signal in an MIMO-OCDM communication system. Constructing a WL-MMSE detector, and detecting the observation signal by using the detector to obtain a corresponding estimation signal; and processing the estimated signal by using an LAS algorithm, and searching an optimal solution in a neighborhood of the estimated signal through successive symbol flipping and likelihood function optimization to complete detection. According to the invention, high signal-to-noise ratio gain is realized, the actual operation complexity is greatly reduced, and the method is more suitable for high-speed, low-delay and high-capacity 6G application scenarios.

Description

Technical Field

[0001] The present invention relates to the technical field of wireless communications, and in particular to a detection method and system of a MIMO-OCDM detector based on wide linear minimum mean square error. Background Art

[0002] Chirp signals have high processing gain, low power consumption, robustness against channel impairments, and good autocorrelation characteristics, so they have been widely used in the fields of radar and communication. At present, there are many ways to use Chirp signals for communication. A direct method is non-overlapping linear frequency modulation pulses modulated by FSK (Frequency-shifted keying). This system is widely used in radar detection, but this method will lead to problems such as low spectrum efficiency of the system. To address this problem, Chirp signals can use their orthogonality to superimpose in the time domain or frequency domain to improve spectrum efficiency and data rate, which is the OCDM system.

[0003] With the development of 6G communication networks, MIMO-OCDM (Multiple-Input Multiple-Output-Orthogonal Chirp-Division Multiplexing) has attracted much attention due to its anti-interference characteristics in multipath channel environments, efficient use of spectrum resources, and low peak-to-average ratio. However, MIMO-OCDM systems in high dimensions face a trade-off between complexity and bit error rate when designing detectors. Although maximum likelihood detection can provide optimal detection results, its high computational complexity limits its application in large-scale MIMO systems. Traditional MMSE (Minimum-mean-square-error) detectors have relatively low complexity, but their performance is limited in non-circular signal processing. Summary of the invention

[0004] The purpose of the present invention is to provide a detection method and system for a MIMO-OCDM detector based on wide linear minimum mean square error, which combines WL-MMSE (Widely Linear-Minimum-mean-square-error) and LAS (Likelihood Ascent Search) algorithms, and makes the detector more applicable in 6G large-scale MIMO scenarios by improving detection accuracy and reducing computational complexity, meeting the communication requirements of low latency and high precision, and being able to achieve near-optimal detection effects while maintaining low complexity.

[0005] The present invention adopts the following technical solution:

[0006] A detection method of a MIMO-OCDM detector based on wide linear minimum mean square error comprises the following steps:

[0007] S1. Through discrete Fresnel change, the signal received by the receiving antenna is demodulated to obtain the observation signal in the MIMO-OCDM communication system.

[0008] S2. Construct a WL-MMSE detector, and use the detector to detect the observed signal in step S1 to obtain a corresponding estimated signal.

[0009] S3. The estimated signal in step S2 is processed using the LAS algorithm, and the optimal solution is searched in the neighborhood of the estimated signal by successive sign flipping and likelihood function optimization to complete the detection.

[0010] Furthermore, in step S1, obtaining the observation signal includes the following contents:

[0011] S101, set the MIMO-OCDM communication system to include M T transmit antennas and M R There are receiving antennas, and each transmitting antenna transmits N orthogonal Chirp subcarriers. The symbol sequence s transmitted by the subcarrier is expressed as in Indicates the Mth T The transpose of the symbol sequence transmitted by the subcarriers of the transmit antennas.

[0012] S102, using DFnT to perform OCDM modulation on the modulation symbol data signal to generate an orthogonal linear frequency modulation signal, and add a cyclic prefix, the orthogonal linear frequency modulation signal on the qth transmitting antenna It is expressed as:

[0013]

[0014] Among them, s q represents the symbol sequence transmitted by the subcarrier of the qth transmitting antenna, Φ q represents the set of diagonal IDFnT matrices for the qth transmit antenna, (m,n) represents Φ q The number of elements in , Represents Φ q The inverse transform of .

[0015] S103, orthogonal linear frequency modulation signal x OCDM When propagating in a multipath channel, the signal r received by the receiving antenna is expressed as:

[0016]

[0017] in, Indicates the Mth R The transpose of the signal received by the receiving antenna; Λ represents the channel coefficient matrix, Indicates the Mth T The transmitting antenna to the Mth R The channel coefficients between the receiving antennas; n represents the additive white Gaussian noise vector, Indicates the Mth R Gaussian white noise received by the receiving antennas; represents the set of diagonal IDFnT matrices for the transmit antennas, Indicates the Mth T The IDFnT matrix corresponding to the transmitting antennas.

[0018] Perform DFnT operation on r to obtain the observed signal. The specific formula is:

[0019] r′=Φ R r

[0020] Where r′ represents the observation signal received by the receiving antenna; Φ R represents the set of diagonal DFnT matrices of receiving antennas, Indicates the Mth R The DFnT matrix corresponding to the receiving antennas.

[0021] Furthermore, in step S2, obtaining the estimated signal includes the following contents:

[0022] S201, based on the channel state information and the complex conjugate information of the observation signal, combined with the MIMO-OCDM detector and the MMSE criterion, a WL-MMSE detector is constructed, and the matrix expression of the detector is:

[0023]

[0024] Among them, W WL-MMSE represents the WL-MMSE detection matrix; represents the augmented form of the equivalent channel matrix, Θ T represents the transpose of the equivalent channel matrix, Θ H represents the conjugate transpose of the equivalent channel matrix; represents the noise variance; Represents the identity matrix.

[0025] S202, the WL-MMSE detector processes the observed signal to obtain a corresponding estimated signal. The specific formula is:

[0026]

[0027] Where y represents the estimated signal; represents the augmented vector of the observed signal, r ′* represents the conjugate form of the observed signal.

[0028] Furthermore, in step S3, obtaining the optimal solution includes the following contents:

[0029] S301, obtaining an initial vector from the output of the WL-MMSE detector, the specific formula is:

[0030]

[0031] in, represents the initial vector of the LAS algorithm, NM T Indicates the total length of a vector; [] Ω Represents the operation of quantizing the initial vector to the nearest BPSK constellation point.

[0032] S302, from the initial vector Initially, when the likelihood change from the nth iteration to the n+1th iteration is positive, Updated to Perform step-by-step iteration until a fixed point is reached; the specific expression is:

[0033]

[0034] in, represents the change in likelihood from the nth iteration to the n+1th iteration; represents the likelihood function, represents the detection vector, express The transpose of eff =Θ H r′+(Θ H r′) * , Θ eff =Θ H Θ; represents the likelihood function value of the nth iteration; Represents the likelihood function value of the n+1th iteration.

[0035] definition but Further expressed as:

[0036]

[0037] Where L(n) represents the vector length; g(n) represents the gradient of the likelihood function at the i-th bit position, represents the real part of the signal, represents the detection vector obtained after the nth iteration of the i-th bit position, represents the detection vector obtained after the n+1th iteration of the i-th bit position, represents the likelihood function value of the ith bit position after the nth iteration, i represents the bit position of the matrix, i=1,...NM T .

[0038] When the detection vector meets the flipping condition, it is flipped to ensure that the likelihood function increases monotonically; the expression of the flipping condition is:

[0039]

[0040] Among them, t i (n) represents the threshold value of the i-th bit position,

[0041] When the result meets the convergence condition, the iteration is stopped and the optimized detection vector is obtained. This is the optimal solution.

[0042] Furthermore, the present invention also proposes a detection system of a MIMO-OCDM detector based on a wide linear minimum mean square error, comprising:

[0043] The observation signal acquisition module demodulates the signal received by the receiving antenna through discrete Fresnel change to obtain the observation signal in the MIMO-OCDM communication system.

[0044] The estimated signal acquisition module is used to construct a WL-MMSE detector, and the detector is used to detect the observation signal in the observation signal acquisition module to obtain a corresponding estimated signal.

[0045] The detection module is used to process the estimated signal in the estimated signal acquisition module using the LAS algorithm, and to search for the optimal solution in the neighborhood of the estimated signal through successive sign flipping and likelihood function optimization to complete the detection.

[0046] Furthermore, the present invention also proposes an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the detection method of the MIMO-OCDM detector based on wide linear minimum mean square error when executing the computer program.

[0047] Furthermore, the present invention also proposes a computer-readable storage medium, which stores a computer program, characterized in that when the computer program is run by a processor, it executes the detection method of the MIMO-OCDM detector based on wide linear minimum mean square error.

[0048] Compared with the prior art, the present invention adopts the above technical solution and has the following technical effects:

[0049] 1. The detector proposed in the present invention has better BER (Bit Error Rate) performance and can achieve similar ML detection effect with low complexity.

[0050] 2. In the present invention, the combination of WL-MMSE and LAS significantly improves the SNR gain of the MIMO-OCDM system, achieving a higher signal-to-noise ratio gain.

[0051] 3. The present invention further optimizes detection based on WL-MMSE through the LAS algorithm, which is suitable for real-time detection of large-scale MIMO-OCDM systems, greatly reduces the actual calculation complexity, can obtain better detection results within a smaller number of iterations, and effectively reduces the calculation time.

[0052] 4. The present invention is more suitable for high-speed, low-latency, and high-capacity 6G application scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 It is an overall implementation flow chart of the detector of the present invention.

[0054] Figure 2 It is a comparison chart of BER performance of different detectors under 4×4 and 8×8 antennas of the present invention.

[0055] Figure 3 3 is an iterative convergence performance diagram of the LAS algorithm under different signal-to-noise ratios according to an embodiment of the present invention. DETAILED DESCRIPTION

[0056] The present invention will be further described below in conjunction with the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and cannot be used to limit the protection scope of the present invention.

[0057] In view of the unique properties of non-circular signals, the concept of WL (Widely Linear) has also emerged, and has aroused great research interest in wireless communication systems in recent years. The main principle of WL is to provide a new DoF (Degree of Free) for system optimization design by jointly optimizing the signal itself and its complex conjugate. When the communication system sends non-circular signals, WL can often produce a performance gain of more than twice that of linear processing. At the receiving end, a wide linear detector based on the MMSE criterion is also proposed, which proves that it has further performance improvements in mean square error, symbol error rate, and achievable multiplexing gain compared to linear detectors.

[0058] To achieve the above object, the present invention proposes a detection method of a MIMO-OCDM detector based on wide linear minimum mean square error, such as Figure 1 As shown, the specific steps are as follows:

[0059] S1. Through discrete Fresnel change, the signal received by the receiving antenna is demodulated to obtain the observation signal in the MIMO-OCDM communication system. The specific contents are:

[0060] S101、MIMO-OCDM communication system has M T transmit antennas and M R Each transmitting antenna transmits N orthogonal Chirp subcarriers, and the symbol sequence s transmitted by all subcarriers is expressed as in Indicates the Mth T The transpose of the symbol sequence transmitted by the subcarriers of the transmit antennas.

[0061] S102, using DFnT (Discrete Fresnel Transform) to perform OCDM modulation on the modulation symbol data signal, i.e., BPSK (Binary Phase Shift Keying) signal, to generate an orthogonal linear frequency modulation signal, and adding CP (Cyclic Prefix) to reduce the impact of multipath interference; similar to the OFDM-based system, CP is added to the OCDM block to combat multipath propagation, assuming that the receiving end can synchronously obtain channel state information through a specific channel estimation method. Orthogonal linear frequency modulation signal on the qth transmitting antenna It can be expressed as:

[0062]

[0063] Among them, s q represents the symbol sequence transmitted by the subcarrier of the qth transmitting antenna, The corresponding DFnT matrix of the qth transmit antenna is shown, represents its inverse transformation.

[0064] The DFnT matrix Φ(m,n) containing (m,n) elements is defined as:

[0065]

[0066] S103, orthogonal linear frequency modulation signal x OCDM Propagation in a multipath channel, therefore, the signal r received by the receiving antenna can be expressed as:

[0067]

[0068] in, Indicates the Mth R The transpose of the signal received by the receiving antenna; Λ represents the channel coefficient matrix, Indicates the Mth T The transmitting antenna to the Mth R The channel coefficients between the receiving antennas; n represents the additive white Gaussian noise vector, Indicates the Mth R Gaussian white noise received by the receiving antennas; represents the set of diagonal IDFnT matrices for the transmit antennas, Indicates the Mth T The IDFnT matrix corresponding to the transmitting antennas.

[0069] Perform DFnT operation on r to obtain the observed signal. The specific formula is:

[0070]

[0071] Where r′ represents the observation signal received by the receiving antenna; Φ R represents the set of diagonal DFnT matrices of receiving antennas, Indicates the Mth R The DFnT matrix corresponding to the receiving antennas; Θ represents the equivalent channel matrix, n′ represents Gaussian white noise in the Fresnel domain.

[0072] S2. Construct a WL-MMSE detector and use it to detect the observed signal to obtain the corresponding estimated signal. The specific contents are:

[0073] S201, based on the channel state information and the complex conjugate information of the observation signal, combined with the MIMO-OCDM detector and the MMSE criterion, a WL-MMSE detector is constructed, and the matrix expression of the detector is:

[0074]

[0075] Among them, W WL-MMSE represents the WL-MMSE detection matrix; The augmented form of the equivalent channel matrix is ​​expressed as where Θ T represents the transpose of the equivalent channel matrix, Θ H represents the conjugate transpose of the equivalent channel matrix; represents the noise variance; Represents the identity matrix.

[0076] S202, the WL-MMSE detector processes the observed signal to obtain a corresponding estimated signal. The specific formula is:

[0077]

[0078] Where y represents the estimated signal; represents the augmented vector of the observed signal, r ′* represents the conjugate form of the observed signal.

[0079] S3, LAS algorithm neighborhood search. The estimated signal in step S2 is processed using the LAS algorithm, and the optimal solution is gradually searched in the neighborhood of the estimated signal by successive sign flipping and likelihood function optimization. The specific contents are:

[0080] S301, the initial vector can be obtained from the output of the WL-MMSE detector, expressed as:

[0081]

[0082] in, Represents the initial vector of the LAS algorithm, [] Ω Represents the operation of quantizing the initial vector to the nearest BPSK constellation point.

[0083] S302, from the initial vector Initially, the LAS algorithm passes Updated to To gradually select until a fixed point is reached. The update rule of LAS is that when the likelihood changes from step n to n+1 When is positive, update, that is:

[0084]

[0085] in, represents the change in likelihood from the nth iteration to the n+1th iteration; represents the likelihood function, r′ eff =Θ H r′+(Θ H r′) * , Θ eff =Θ H Θ, represents the detection vector, express The transpose of represents the likelihood function value of the nth iteration; Represents the likelihood function value of the n+1th iteration.

[0086] definition thereby can be rewritten as:

[0087]

[0088] Where L(n) represents the vector length; g(n) represents the gradient of the likelihood function at the i-th bit position, represents the real part of the signal, Represents the detection vector obtained after the nth iteration. i represents the bit position of the matrix, i=1,...NM T , N.M. T Represents the total length of the vector.

[0089] The update rule of the LAS algorithm can be systematically constructed to ensure that the likelihood function is monotonically increasing (i.e. ), provided that at least one bit s i (n) is flipped, and the flip condition expression is:

[0090]

[0091] Among them, t i (n) represents the threshold value of the i-th bit position,

[0092] The convergence property of the LAS algorithm ensures that the detection process is completed in a short time. When the result meets the convergence condition, the iteration stops, which means that only a certain subset of bits are continuously flipped between +1 and -1. The optimized symbol vector is output as the optimal solution.

[0093] Figure 2(a) is the performance bit error rate BPSK constellation diagram obtained using different WL-MMSE-LAS detectors under 4×4 antennas. Figure 2 (b) is the performance bit error rate BPSK constellation diagram obtained by using different WL-MMSE-LAS detectors under 8×8 antennas. It can be seen from the figure that compared with the traditional MIMO-OFDM system, the combination of WL-MMSE and LAS detection methods significantly improves the SNR gain of the MIMO-OCDM system, and the WL-MMSE detector is significantly better than the MMSE detector. -3 The WL-MMSE detector also shows superior performance compared to the WL-MMSE-LAS detector. -4 By adding LAS receiver after MMSE and WL-MMSE detectors, the signal-to-noise ratio gain of 4 dB is achieved at 10 -4 In addition, compared with other detectors, WL-MMSE-LAS can achieve 8dB and 3dB signal-to-noise ratio gains when applied to MIMO-OCDM systems at a BER of 10 -4 A gain of 7dB was achieved, further highlighting its advantages and proving that the method proposed in the present invention is more suitable for high-speed, low-latency, and high-capacity 6G application scenarios.

[0094] Figure 3 This is the iterative convergence performance diagram of the LAS algorithm under different signal-to-noise ratios. Through further detection optimization based on WL-MMSE, the LAS algorithm is suitable for real-time detection of large-scale MIMO-OCDM systems, which greatly reduces the actual computational complexity. The LAS algorithm has the characteristics of fast convergence and can obtain better detection results within a small number of iterations, effectively reducing the computational time.

[0095] The WL-MMSE-LAS detector of the present invention is suitable for large-scale MIMO-OCDM environments in high-bandwidth, high-rate, and high-capacity 6G communication systems, and is particularly suitable for the following scenarios:

[0096] High mobility scenarios: In high-speed mobile environments such as vehicle communications, drone communications, and high-speed rail communications in 6G networks, the detector of the present invention can adapt to rapid changes in channels through rapid neighborhood searches to ensure the stability of signal detection.

[0097] High-density scenarios: In high-density networks such as city centers and stadiums, the traditional ML detector has too high computational complexity. The WL-MMSE-LAS detector can effectively improve the error performance while maintaining low complexity and adapt to high user density and interference environments.

[0098] Low-latency communication: The WL-MMSE-LAS detector of the present invention is suitable for 6G applications with low latency requirements, such as industrial automation, remote surgery, and virtual reality (VR) communication. The fast convergence characteristics of the LAS algorithm can significantly shorten the detection delay and ensure the real-time performance of the system.

[0099] The embodiment of the present invention also proposes a detection system of a MIMO-OCDM detector based on a wide linear minimum mean square error, including an observation signal acquisition module, an estimation signal acquisition module, a detection module, and a computer program that can be run on a processor. It should be noted that each module in the above system corresponds to the specific steps of the method provided in the embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method. For technical details not described in detail in this embodiment, please refer to the method provided in the embodiment of the present invention.

[0100] The embodiment of the present invention further provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. It should be noted that when the processor executes the computer program, the specific steps of the method provided in the embodiment of the present invention are corresponding to the specific steps of the method provided in the embodiment of the present invention, and the processor has the functional modules and beneficial effects corresponding to the execution method. For technical details not described in detail in this embodiment, please refer to the method provided in the embodiment of the present invention.

[0101] The embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program. It should be noted that when the computer program is executed by the processor, it corresponds to the specific steps of the method provided in the embodiment of the present invention, and has the functional modules and beneficial effects corresponding to the execution method. For technical details not described in detail in this embodiment, please refer to the method provided in the embodiment of the present invention.

[0102] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A detection method for a MIMO-OCDM detector based on wide linear minimum mean square error, characterized in that: include: S1. Demodulate the signal received by the receiving antenna through discrete Fresnel change to obtain the observation signal in the MIMO-OCDM communication system; S2, constructing a WL-MMSE detector, and using the detector to detect the observed signal in step S1 to obtain a corresponding estimated signal; S3. The estimated signal in step S2 is processed using the LAS algorithm, and the optimal solution is searched in the neighborhood of the estimated signal by successive sign flipping and likelihood function optimization to complete the detection.

2. The detection method of the MIMO-OCDM detector based on wide linear minimum mean square error according to claim 1, characterized in that: In step S1, obtaining the observation signal includes the following contents: S101, set the MIMO-OCDM communication system to include M T transmit antennas and M R There are receiving antennas, and each transmitting antenna transmits N orthogonal Chirp subcarriers. The symbol sequence s transmitted by the subcarrier is expressed as in Indicates the Mth T The transposition of the symbol sequence transmitted by the subcarriers of the transmitting antennas; S102, using DFnT to perform OCDM modulation on the modulation symbol data signal to generate an orthogonal linear frequency modulation signal, and add a cyclic prefix, the orthogonal linear frequency modulation signal on the qth transmitting antenna It is expressed as: Among them, s q represents the symbol sequence transmitted by the subcarrier of the qth transmitting antenna, Φ q represents the set of diagonal IDFnT matrices for the qth transmit antenna, (m,n) represents Φ q The number of elements in , Represents Φ q The inverse transformation of S103, orthogonal linear frequency modulation signal x OCDM When propagating in a multipath channel, the signal r received by the receiving antenna is expressed as: r=Λx OCDM +n in, Indicates the Mth R The transpose of the signal received by the receiving antenna; Λ represents the channel coefficient matrix, Indicates the Mth T The transmitting antenna to the Mth R The channel coefficients between the receiving antennas; n represents the additive white Gaussian noise vector, Indicates the Mth R Gaussian white noise received by the receiving antennas; Perform DFnT operation on r to obtain the observed signal. The specific formula is: r′=Φ R r Where r′ represents the observation signal received by the receiving antenna; Φ R represents the set of diagonal DFnT matrices of receiving antennas, Indicates the Mth R The DFnT matrix corresponding to the receiving antennas.

3. The detection method of the MIMO-OCDM detector based on wide linear minimum mean square error according to claim 1, characterized in that: In step S2, obtaining the estimated signal includes the following contents: S201, based on the channel state information and the complex conjugate information of the observation signal, combined with the MIMO-OCDM detector and the MMSE criterion, a WL-MMSE detector is constructed, and the matrix expression of the detector is: Among them, W WL-MMSE represents the WL-MMSE detection matrix; represents the augmented form of the equivalent channel matrix, Θ T represents the transpose of the equivalent channel matrix, Θ H represents the conjugate transpose of the equivalent channel matrix; represents the noise variance; represents the identity matrix; S202, the WL-MMSE detector processes the observed signal to obtain a corresponding estimated signal. The specific formula is: Where y represents the estimated signal; represents the augmented vector of the observed signal, r ′* represents the conjugate form of the observed signal.

4. The detection method of the MIMO-OCDM detector based on wide linear minimum mean square error according to claim 1, characterized in that: In step S3, the optimal solution includes the following contents: S301, obtaining an initial vector from the output of the WL-MMSE detector, the specific formula is: in, represents the initial vector of the LAS algorithm, NM T represents the total length of the vector; y represents the estimated signal; [] Ω represents the operation of quantizing the initial vector to the nearest BPSK constellation point; S302, from the initial vector Initially, when the likelihood change from the nth iteration to the n+1th iteration is positive, Will Updated to Perform step-by-step iteration until a fixed point is reached; the specific expression is: Where ΔΛ(s(n)) represents the change in likelihood from the nth iteration to the n+1th iteration; represents the likelihood function, represents the detection vector, express The transpose of represents the likelihood function value of the nth iteration; represents the likelihood function value of the n+1th iteration; definition but Further expressed as: Where L(n) represents the vector length; g(n) represents the gradient of the likelihood function at the i-th bit position, represents the real part of the signal, represents the detection vector obtained after the nth iteration of the i-th bit position, represents the detection vector obtained after the n+1th iteration of the i-th bit position, Represents the likelihood function value of the i-th bit position after the n-th iteration, i represents the bit position of the matrix, i=1, NM T ; When the detection vector meets the flipping condition, it is flipped to ensure that the likelihood function increases monotonically; the expression of the flipping condition is: Among them, t i (n) represents the threshold value of the i-th bit position, When the result meets the convergence condition, the iteration is stopped and the optimized detection vector is obtained. This is the optimal solution.

5. A system for the detection method of the MIMO-OCDM detector based on wide linear minimum mean square error according to claim 1, characterized in that: include: The observation signal acquisition module demodulates the signal received by the receiving antenna through discrete Fresnel change to obtain the observation signal in the MIMO-OCDM communication system; The estimation signal acquisition module is used to construct a WL-MMSE detector, and the detector is used to detect the observation signal in the observation signal acquisition module to obtain a corresponding estimation signal; The detection module is used to process the estimated signal in the estimated signal acquisition module using the LAS algorithm, and to search for the optimal solution in the neighborhood of the estimated signal through successive sign flipping and likelihood function optimization to complete the detection.

6. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the detection method of the MIMO-OCDM detector based on wide linear minimum mean square error according to any one of claims 1 to 4 are implemented.

7. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the detection method of the MIMO-OCDM detector based on wide linear minimum mean square error according to any one of claims 1 to 4 is executed.

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