WO2023236610A1 - 信号检测方法、装置、电子设备及存储介质 - Google Patents

信号检测方法、装置、电子设备及存储介质 Download PDF

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Publication number
WO2023236610A1
WO2023236610A1 PCT/CN2023/080785 CN2023080785W WO2023236610A1 WO 2023236610 A1 WO2023236610 A1 WO 2023236610A1 CN 2023080785 W CN2023080785 W CN 2023080785W WO 2023236610 A1 WO2023236610 A1 WO 2023236610A1
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WIPO (PCT)
Prior art keywords
point set
constellation point
probability
nearest neighbor
received signal
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PCT/CN2023/080785
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English (en)
French (fr)
Inventor
张川
葛荧萌
刘李汉唐
冀贞昊
张在琛
黄永明
尤肖虎
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网络通信与安全紫金山实验室
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Publication of WO2023236610A1 publication Critical patent/WO2023236610A1/zh

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Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/0413—MIMO systems
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H04B7/0613—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission
    • H04B7/0615—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal
    • H04B7/0619—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal using feedback from receiving side
    • H04B7/0621—Feedback content
    • H04B7/0626—Channel coefficients, e.g. channel state information [CSI]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H04B7/0613—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission
    • H04B7/0615—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal
    • H04B7/0619—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal using feedback from receiving side
    • H04B7/0621—Feedback content
    • H04B7/063—Parameters other than those covered in groups H04B7/0623 - H04B7/0634, e.g. channel matrix rank or transmit mode selection
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

Definitions

  • the present disclosure relates to the field of communication technology, and in particular, to a signal detection method, device, electronic equipment and storage medium.
  • the digital signal processor (Digital Signal Processer, DSP) in the terminal equipment generally uses the Massive-Multiple Input Multiple Output (M-MIMO) detection algorithm to detect the transmission signal of the terminal equipment.
  • M-MIMO detection algorithm may include but is not limited to the Maximum Likelihood (ML) algorithm, the Maximum A Posterior (MAP) algorithm, and the Message Passing Detection (MPD) based on Bayesian inference. )algorithm.
  • the terminal device uses the ML algorithm, the MAP algorithm, or the MPD algorithm based on Bayesian reasoning to detect the transmission signal of the terminal device
  • the hardware implementation of the digital signal processor is difficult, and the entire signal detection The process is relatively complicated, making it impossible to accurately detect the transmission signal of the terminal device.
  • the present disclosure provides a signal detection method, device, electronic equipment and storage medium to solve the problem in related technologies that a terminal equipment uses an M-MIMO detection algorithm to detect the transmission signal of the terminal equipment. Since the entire signal detection process is relatively complex, it causes When accurately detecting a signal, the corresponding detection hardware cost is relatively high.
  • This disclosure uses a low-complexity design concept to design a relatively simplified signal detection device.
  • the signal detection device can include a selector, a calculator and a parallel interference canceller, so that This enables low-complexity and high-accuracy detection of signals in terminal equipment.
  • the present disclosure provides a signal detection method, including:
  • the target symbol parameters corresponding to the received signal are determined
  • the target symbol parameters determine the probability corresponding to the received signal in the modulation symbol constellation point set
  • the estimated value corresponding to the transmitted signal is determined.
  • the present disclosure also provides a signal detection device, including:
  • a selection module configured to determine the target symbol parameters corresponding to the received signal during the process of detecting the transmission signal of the terminal device
  • a calculation module configured to determine the probability corresponding to the received signal in the modulation symbol constellation point set based on the target symbol parameters
  • the parallel interference cancellation module is configured to determine the estimated value corresponding to the transmitted signal based on the probability.
  • the present disclosure also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor.
  • the processor includes a selector, a calculator, and a parallel interference canceller.
  • the processor When the program is executed, any one of the above signal detection methods is implemented.
  • the present disclosure also provides a non-transitory computer-readable storage medium on which a computer program is stored.
  • a computer program is stored on which a computer program is stored.
  • the computer program is executed by a processor, any one of the above signal detection methods is implemented.
  • the present disclosure also provides a computer program product, which includes a computer program.
  • the computer program When the computer program is executed by a processor, the computer program implements any one of the above signal detection methods.
  • the signal detection method, device, electronic equipment and storage medium determine the target symbol parameters corresponding to the received signal in the process of detecting the transmission signal of the terminal device; based on the target symbol parameters, determine the modulation symbol of the received signal. The corresponding probability in the constellation point set; based on this probability, the estimated value corresponding to the transmitted signal is determined.
  • the above method is used to solve the problem in the related art that the terminal equipment uses the M-MIMO detection algorithm to detect the transmission signal of the terminal equipment. Since the entire signal detection process is relatively complicated, the corresponding detection hardware cost for accurate signal detection is relatively high. , the present disclosure designs a relatively simplified signal detection device through low-complexity design ideas.
  • the signal detection device includes a selector, a calculator and a parallel interference canceller, so that low complexity and high accuracy can be achieved for signals in terminal equipment. Detection degree.
  • Figure 1a is one of the structural schematic diagrams of the signal detection device provided by the present disclosure.
  • Figure 1b is a schematic structural diagram of a constellation processing element provided by the present disclosure
  • Figure 1c is a schematic structural diagram of a parallel interference canceller provided by the present disclosure
  • FIG. 2 is one of the flow diagrams of the signal detection method provided by the present disclosure
  • Figure 3a is the second schematic flow chart of the signal detection method provided by the present disclosure.
  • Figure 3b is one of the performance simulation diagrams corresponding to the signal detection method provided by the present disclosure.
  • Figure 3c is the second performance simulation diagram corresponding to the signal detection method provided by the present disclosure.
  • Figure 3d is the third schematic diagram of performance simulation corresponding to the signal detection method provided by the present disclosure.
  • Figure 4a is the third schematic flow chart of the signal detection method provided by the present disclosure.
  • Figure 4b is a schematic diagram of the simulation results provided by the present disclosure.
  • Figure 5 is the second structural schematic diagram of the signal detection device provided by the present disclosure.
  • FIG. 6 is a schematic structural diagram of an electronic device provided by the present disclosure.
  • MPD algorithms may include but are not limited to: Belief Propagation (BP) signal detection algorithm, Channel Hardening-Exploiting Message Passing (CHEMP) signal detection algorithm and Approximate Message Passing ( Approximate Message Passing, AMP) signal detection algorithm, etc.
  • BP Belief Propagation
  • CHEMP Channel Hardening-Exploiting Message Passing
  • Approximate Message Passing Approximate Message Passing
  • the AMP signal detection algorithm was first used to solve the Least Absolute Shrinkage and Selection Operator (LASSO) problem. In addition, it can also be used to solve sparse signal recovery and compressed sensing problems.
  • LASSO Least Absolute Shrinkage and Selection Operator
  • the terminal device uses the AMP signal detection algorithm to detect the transmission signal of the terminal device, the terminal device cannot accurately calculate the moment matching. Therefore, the terminal device cannot accurately detect the transmission information.
  • the signal detection device 10 includes: a controller unit (Control Unit, CU) 101, an iteration unit 102 and a register unit 103.
  • a controller unit Control Unit, CU 101
  • an iteration unit 102 and a register unit 103.
  • the controller unit 101 is configured to control the clock and input/output (I/O);
  • the iteration unit 102 is configured to determine the target symbol parameters corresponding to the received signal in each iterative update, the corresponding probability in the modulation symbol constellation point set, and the estimated value corresponding to the transmitted signal;
  • the register unit 103 is configured to store I/O and auxiliary data.
  • the auxiliary data may include but is not limited to the above purposes. Symbol parameters, probabilities and estimates.
  • the iteration unit 102 may include: a constellation processing element 1021 and a parallel interference cancellation element 1022.
  • the number of constellation processing elements 1021 is p
  • the number of parallel interference cancellation elements 1022 is q.
  • the value of p is 4, which are the first constellation processing element, the second constellation processing element, the third constellation processing element and the fourth constellation processing element respectively
  • the value of q is 4, which are the first constellation processing element respectively.
  • the register unit 103 may include: a read-only memory (Read Only Memory, ROM), the number of the register units 103 is s, and the value of s is 4, which are the first register unit, the second register unit, the third register unit and In the fourth register unit, the first register unit is configured to store the matched filter input, the second register unit is configured to store the channel matrix, the third register unit is configured to store the output result, and the fourth register unit is configured to store auxiliary data.
  • ROM Read Only Memory
  • the parallel interference cancellation element 1022 may include: a calculator and a parallel interference canceller, the calculator is configured to determine the probability corresponding to the received signal, and the parallel interference canceller is configured to determine the estimated value corresponding to the transmitted signal.
  • the calculator may include: a numerical change selector and a segment shift selector.
  • the constellation processing element 1021 includes a Nearest Neighbor Approximation (NNA) selector (selector for short), an adder, a multiplier and a selection adder.
  • NNA Nearest Neighbor Approximation
  • the selector is set to determine the target symbol corresponding to the received signal.
  • the adder is set to add operation, the multiplier is set to multiplication operation, and the adder is selected to perform addition operation after selecting data; among them, the adder is connected to the NNA selector and multiplier, and the NNA selector and multiplier are connected to the first
  • the pipeline registers are connected, the first pipeline register is connected to the selection adder, and the selection adder is connected to the second pipeline register.
  • the NNA selector can include multiplexer (MUX)- ⁇ and MUX- ⁇ :
  • the parallel interference canceller may include a mean selector and a matrix-vector multiplier, with the mean selector configured to shift plus branch selection on the data.
  • the signal detection device involved in the embodiment of the present disclosure can use the NNA-AMP algorithm and the hardware-friendly (Hardware-Friendly AMP, HF-AMP) signal detection algorithm to detect the received signal of the terminal device.
  • the NNA-AMP algorithm and the hardware-friendly (Hardware-Friendly AMP, HF-AMP) signal detection algorithm to detect the received signal of the terminal device.
  • the hardware-friendly (Hardware-Friendly AMP, HF-AMP) signal detection algorithm to detect the received signal of the terminal device.
  • Terminal devices involved in the embodiments of the present disclosure may include but are not limited to: mobile terminals, wearable devices, computers, etc.
  • the terminal equipment may be equipped with a narrowband massive multiple-input multiple-output M-MIMO device.
  • the M-MIMO device may include N t transmitting antennas and N r receiving antennas, N t ⁇ 2, N r ⁇ 2, and N t ⁇ N r .
  • the method of modulating the received signal of the terminal device includes modulating a set of symbol constellation points.
  • constellation point set is a Q-symbol quadrature amplitude modulation (Q-Quadrature Amplitude Modulation, Q-QAM) method of ⁇ .
  • the mean value corresponding to n is 0, and the noise variance corresponding to n is 1/N r , at this time, Represents the additive white Gaussian Noise (AWGN) vector, The corresponding mean is 0, The corresponding noise variance is represents the identity matrix.
  • AWGN additive white Gaussian Noise
  • the value of Q among the Q symbols can be one of 16, 32, 64, and 256, which is not specifically limited here.
  • H represents the transmission matrix corresponding to the wireless communication channel of the terminal device.
  • the dimension of the transmission matrix is 2N r ⁇ 2N t , H ⁇ R 2Nr ⁇ 2Nt .
  • the execution subject involved in the embodiment of the present disclosure may be a signal detection device or a terminal device.
  • the following takes a terminal device as an example to further describe the embodiments of the present disclosure.
  • FIG. 2 it is a schematic flow chart of the signal detection method provided by the present disclosure, which may include:
  • the target symbol parameters may include: modulation symbol constellation point set nearest neighbor symbol ⁇ in , or, the The corresponding encoding flag is F.
  • the terminal device can use the selector to select the auxiliary data included in the register unit. , determine ⁇ ; it can also be based on the Corresponding position index m, determine the corresponding Encoding flags are not specifically limited here.
  • the terminal device may, according to the first preset number of location indexes m, The nearest neighbor symbol ⁇ corresponding to m is determined in , and the number of ⁇ is the same as the number of m; it is also possible to determine Divide to obtain a second preset number of intervals, and mark the second preset number of intervals with corresponding Gray codes to obtain a second preset number of coding flags F, which are not specifically limited here.
  • the first preset quantity and the second preset quantity may be the same or different.
  • the first preset quantity and the second preset quantity may be set before the terminal device leaves the factory, or may be set by the user according to actual needs. defined, there is no specific limitation here.
  • the target symbol parameters determine the corresponding probability of the received signal in the modulation symbol constellation point set.
  • the terminal device may first determine the relationship parameter corresponding to the received signal according to the target symbol parameter, and then determine the probability corresponding to the received signal in the modulation symbol constellation point set based on the relationship parameter.
  • the terminal device may determine the first probability corresponding to the received signal based on the above ⁇ , or may determine the second probability corresponding to the received signal based on the above F, which is not specifically limited here.
  • the terminal device can determine the first probability corresponding to the received signal in the modulation symbol constellation point set according to the first relationship parameter corresponding to ⁇ , or can determine the first probability corresponding to the received signal in the modulation symbol according to the second relationship parameter corresponding to F.
  • the corresponding second probability in the symbol constellation point set is not specifically limited here.
  • the terminal device can determine the probability corresponding to the received signal using G and b.
  • the terminal device may determine the detection error corresponding to the transmitted signal based on probability, and then determine the estimated value corresponding to the transmitted signal based on the detection error.
  • the terminal device may first determine the mean value corresponding to the received signal based on probability, and then determine the detection error corresponding to the received signal based on the mean value.
  • detect error It can be obtained by the terminal equipment using the mean selector in the parallel interference canceller.
  • the terminal device uses the first adder to combine the output of the addition tree with the filtered received signal bi to obtain the detection error.
  • estimated value It can be obtained by the terminal equipment using the matrix vector multiplier in the parallel interference canceller.
  • g i represents the i-th row element in G.
  • the above method is used to solve the problem in the related art that the terminal equipment uses the M-MIMO detection algorithm to detect the transmission signal of the terminal equipment. Since the entire signal detection process is relatively complicated, it leads to problems in accurately detecting the signal. The corresponding detection hardware is relatively expensive.
  • This disclosure uses low-complexity design ideas to design a relatively simplified signal detection device.
  • the signal detection device can include a selector, a calculator and a parallel interference canceller, so that the signal detection device in the terminal device can be detected. Signals can be detected with low complexity and high accuracy.
  • FIG. 3a it is a schematic flow chart of the signal detection method provided by the present disclosure, which may include:
  • the terminal device can use the selector to set the modulation symbol constellation points according to the first preset number of position indexes m. , determine the nearest neighbor symbol ⁇ corresponding to m.
  • the first preset number is 2.
  • the terminal device can be based on two location indexes, namely the first location index m 1 and the second location index m 2 .
  • the first nearest neighbor symbol ⁇ m1 corresponding to m 1 is determined, and the second nearest neighbor symbol ⁇ m2 corresponding to m 2 is determined.
  • m 1 and m 2 are randomly selected by the terminal device.
  • the terminal device may first delete some processing nodes with low performance dependency from the SFG to achieve the purpose of compressing the processing nodes and thereby improve the processing efficiency of other processing nodes.
  • the terminal device can Obtain the noise variance ⁇ (l) corresponding to the terminal device.
  • the ⁇ factor of the transmission model corresponding to the M-MIMO device in the terminal equipment is small, is negligible.
  • the terminal device determines the first relationship parameter according to the nearest neighbor symbol, and determines the first probability corresponding to the received signal in the modulation symbol constellation point set according to the first relationship parameter, which may include: the terminal device determines the first relationship parameter according to the first parameter formula , determine the first relationship parameter, and determine the position of the received signal in the modulation symbol constellation point set according to the first probability formula. corresponding first probability.
  • the first probability formula is m represents the position index, Represents the first probability; Indicates the probability that the received signal corresponds to the modulation symbol constellation point set when the position index is the first nearest neighbor symbol.
  • in the above first parameter formula can be obtained by the terminal device using the value change selector in the calculator, It can be obtained by using the segment shift selector in the calculator on the terminal device.
  • the terminal device in order to simplify the calculation complexity caused by the nonlinear calculation parts such as division and exponent contained in the above-mentioned first parameter formula and the first probability formula, can perform the nonlinear calculation part.
  • Piecewise Linear Approximation allows the terminal device to appropriately approximate some data from the nonlinear part to the linear part within a limited numerical interval to reduce the calculation performance loss of the calculator and improve the accuracy of the calculation results. accuracy.
  • the nonlinear function is The terminal device can first clip ⁇ (l) within the range of [ ⁇ a,1 , ⁇ b,1 ], where eta a,1 represents the first noise threshold and eta b,1 represents the second noise threshold; then, the terminal device Utilizing piecewise linear interpolation function with N seg, 1 segments To approximate the nonlinear function as N seg, 1 represents the first number.
  • the nonlinear function is in, when The value of is small enough, It can be approximately equal to 0.
  • the terminal device can first Cropped within the range [ ⁇ a,2 , ⁇ b,2 ], ⁇ a,2 represents the third noise threshold, eta b,2 represents the fourth noise threshold, and the value of eta b,2 is 0; then, the terminal device uses a piecewise linear function with N seg,2 segments to approximate N seg, 2 represents the second number. That is, the terminal device uses a linear interpolation function to replace the nonlinear function
  • Figure 3b it is a schematic diagram of performance simulation corresponding to the signal detection method provided by the present disclosure.
  • E s represents the average energy of the corresponding symbol of the received signal
  • N 0 represents the channel noise power corresponding to the terminal device.
  • Figure 3c it is a schematic diagram of performance simulation corresponding to the signal detection method provided by the present disclosure.
  • Figure 3c shows a different The corresponding BER change curves respectively.
  • the terminal equipment uses a linear interpolation function to replace the nonlinear function and the corresponding BER is obtained. smaller.
  • FIG. 3d it is a performance simulation diagram corresponding to the signal detection method provided by the present disclosure.
  • the terminal device uses a linear interpolation function to replace the nonlinear function, resulting in a smaller BER.
  • the terminal device may store all the above-mentioned possible related values in a look-up table (Look Up Table, LUT) of the register unit.
  • the terminal device can store all the above possible values in the PLA, and the PLA only needs to store the interval, slope, and intercept. In this case, the amount of data stored in the terminal device is significantly reduced, which can effectively increase the storage space.
  • the method for terminal equipment to obtain corresponding data based on PLA can reduce the processing delay of the entire calculation process to a certain extent, that is, it can reduce the processing delay to a certain extent. Processing time of small multipliers and adders.
  • the estimation formula is represents the estimated value
  • m 1 represents the first position index
  • ⁇ m1 represents the first nearest neighbor symbol corresponding to the first position index
  • m 2 represents the second position index
  • ⁇ m2 represents Indicates the second nearest neighbor symbol corresponding to the second position index
  • the method may also include: the terminal device sends an estimated value corresponding to the signal, and determines the detection error between the sent signal and the output signal.
  • the terminal device sends an estimated value corresponding to the signal and determines the detection error between the sent signal and the output signal, which may include: the terminal device determines the detection error between the sent signal and the output signal according to an error formula.
  • the detection error between the transmission signal and the output signal determined by the electronic device based on the estimated value is also small.
  • the terminal device can use the NNA-AMP algorithm to detect the transmission signal of the terminal device.
  • the above method is used to solve the problem in the related art that the terminal equipment uses the M-MIMO detection algorithm to detect the transmission signal of the terminal equipment. Since the entire signal detection process is relatively complicated, the corresponding detection hardware cost for accurate signal detection is relatively high. , the present disclosure designs a relatively simplified signal detection device through low-complexity design ideas.
  • the signal detection device can include a selector, a calculator and a parallel interference canceller, so that low complexity and high efficiency can be achieved for signals in terminal equipment. Detect with accuracy.
  • FIG. 4a it is a schematic flow chart of the signal detection method provided by the present disclosure, which may include:
  • the terminal device can use the selector to pair the position index m according to the first preset number. Divide to obtain a second preset number of intervals, and mark the second preset number of intervals with corresponding Gray codes to obtain a second preset number of coding flags F.
  • the first preset number is 2, and the second preset number is 6.
  • the terminal device can convert the Divided into 6 intervals, namely (- ⁇ ,-2], (-2,-1], (-1,0], (0,1], (1,2] and (2,+ ⁇ ); Then, the terminal device marks these six intervals with the corresponding Gray codes, and obtains six coding marks F respectively. are F 1 , F 2 , F 3 , F 4 , F 5 and F 6 .
  • ⁇ F 4 , F 5 ⁇ can be obtained by the MUX- ⁇ selector included, and ⁇ F 1 , F 2 , F 3 ⁇ can be obtained by the MUX- ⁇ selector included in the selector.
  • the terminal device can calculate a ⁇ and s ⁇ based on the above six intervals.
  • a ⁇ will have 3 possible values in different intervals, which are -4, 0 and 4 respectively.
  • the terminal device can determine the encoding mark ⁇ F 4 , F 5 ⁇ corresponding to a ⁇ , and ⁇ F 4 , F 5 ⁇ The corresponding Gray codes are 01, 11 and 10 respectively; s ⁇ will have two possible values in different intervals, which are -2 and 2 respectively.
  • the terminal device can determine the coding flag ⁇ F 6 ⁇ corresponding to s ⁇ , and The corresponding Gray codes of ⁇ F 6 ⁇ are 0 and 1 respectively. Therefore, the terminal device can simplify the first parameter formula in step 302 into the second parameter formula.
  • the terminal device can simplify the first parameter formula into the second parameter formula and the first probability formula into the second probability formula. .
  • the terminal device determines the second relationship parameter according to the coding flag, and determines the second probability corresponding to the transmitted signal in the modulation symbol constellation point set according to the second relationship parameter, which may include: the terminal device determines the second relationship parameter according to the second parameter formula, Determine the second relationship parameter, and determine the second probability corresponding to the received signal in the modulation symbol constellation point set according to the second probability formula.
  • the second probability formula is
  • the terminal device will use the linear interpolation function
  • the quantization slope in is taken as 0.5, and the quantization intercept is taken as -0.125.
  • the process by which the terminal device determines the estimated value corresponding to the transmitted signal according to the estimation formula in step 403 is similar to the process by which the terminal device determines the estimated value corresponding to the transmitted signal according to the estimation formula in step 303 shown in Figure 3 and will not be discussed here. Details.
  • the terminal device Since the first relationship parameter in step 302 It has nothing to do with s ⁇ , so the terminal device does not need the encoding flag ⁇ F 6 ⁇ in the process of simplifying the first parameter formula. Then, when the terminal device uses the parallel interference canceller to determine the estimated value corresponding to the transmitted signal, the multiplication operation of the integer constellation can be simplified into a shift and add (Shift And Adder, SAA) operation through subexpression sharing.
  • the electronic device can share the Simplified to a table of means.
  • the mean table is as follows:
  • the method may also include: the terminal device determines, based on probability, that the received signal corresponds to The mean value, and based on the mean value, the detection error between the sent signal and the received signal is determined.
  • the terminal device determines the mean value corresponding to the received signal based on probability, and determines the detection error between the sent signal and the received signal based on the mean value, which may include: the terminal device calculates the mean value corresponding to the received signal according to the mean value table, and Based on the mean, the detection error between the transmitted and received signals is determined.
  • the terminal equipment uses the parallel interference canceller to obtain different average values based on different ⁇ F 1 , F 2 , F 3 ⁇ . Then, the terminal equipment can accurately determine the detection corresponding to the received signal based on the average value. error.
  • the detection error between the transmission signal and the output signal determined by the electronic device based on the estimated value is also small.
  • the modulation mode corresponding to the received signal of the terminal equipment is 16-QAM.
  • the terminal equipment uses the AMP algorithm, NAA-AMP algorithm and HF-AMP algorithm to detect the received signal.
  • the performance parameters of the terminal equipment are basically the same under different iterations of each algorithm, and at the iteration number L- Convergence at 4 o'clock, achieving improved accuracy of transmission information detection.
  • the AMP algorithm can be integrated on the AMP detector
  • the HF-AMP algorithm can be integrated on the HF-AMP detector
  • the HF-AMP algorithm can be integrated on the HF-AMP detector.
  • Figure 4b is a schematic diagram of the simulation results provided by this disclosure.
  • the HF-AMP with 4 fractional and 5 fractional bit widths suffers severe performance degradation.
  • HF-AMP with a 6-bit fractional width almost perfectly restores the performance of floating-point HF-AMP. Therefore, the quantification scheme of HF-AMP is taken as 1-6-6.
  • the HF-AMP detector uses SMIC 65nm LL 1P9M CMOS technology to detect the received signal.
  • the HF-AMP detector is designed and compiled by Synopsys (Design Compile) software, and the results are placed and routed using the Synopsys design process guidance (IC Compiler) software.
  • the annotated toggle rate of the gate-level netlist is converted to the Switching Activity Interchange Format (SAIF) of ambient (Prime-Time) PX to measure pure time-based chip power consumption.
  • SAIF Switching Activity Interchange Format
  • the final hardware corresponding to the HF-AMP detector achieved a high throughput of 10.56Gb/s under a 330MHz clock, which basically reached the highest level in the industry.
  • the overall power consumption was guaranteed to be 103.76mW.
  • the energy consumption per unit bit is ensured to be 9.83pJ/b, achieving an efficient hardware architecture with green features.
  • the terminal device can use the HF-AMP signal detection algorithm to detect the transmission signal of the terminal device.
  • the above method is used to solve the problem in the related art that the terminal equipment uses the M-MIMO detection algorithm to detect the transmission signal of the terminal equipment. Since the entire signal detection process is relatively complicated, the corresponding detection hardware cost for accurate signal detection is relatively high. , the present disclosure designs a relatively simplified signal detection device through low-complexity design ideas.
  • the signal detection device includes a selector, a calculator and a parallel interference canceller, which can achieve low complexity and high accuracy for signals in terminal equipment. ground detection.
  • the signal detection device provided by the present disclosure will be described below.
  • the signal detection device described below and the signal detection method described above can be referred to correspondingly.
  • FIG. 5 it is a schematic structural diagram of the signal detection device provided by the present disclosure, which may include:
  • the selection module 501 is configured to determine the target symbol parameters corresponding to the received signal during the process of detecting the transmission signal of the terminal device;
  • the calculation module 502 is configured to determine the probability corresponding to the received signal in the modulation symbol constellation point set according to the target symbol parameters
  • the parallel interference cancellation module 503 is configured to determine the estimated value corresponding to the transmitted signal based on the probability.
  • the selection module 501 is specifically configured to determine the nearest neighbor symbol corresponding to the received signal in the modulation symbol constellation point set; or, according to the position index corresponding to the modulation symbol constellation point set, determine the position index of the received signal in the modulation symbol constellation point set.
  • the corresponding coding mark in the symbol constellation point set number is specifically configured to determine the nearest neighbor symbol corresponding to the received signal in the modulation symbol constellation point set; or, according to the position index corresponding to the modulation symbol constellation point set, determine the position index of the received signal in the modulation symbol constellation point set.
  • the calculation module 502 is specifically configured to determine a first relationship parameter based on the nearest neighbor symbol, and determine a first probability corresponding to the received signal in the modulation symbol constellation point set based on the first relationship parameter.
  • the calculation module 502 is specifically configured to determine the first relationship parameter according to the first parameter formula, and determine the first probability corresponding to the received signal in the modulation symbol constellation point set according to the first probability formula;
  • the first The parameter formula is l represents the number of iterations, represents the first relationship parameter, m 1 represents the first position index, ⁇ m1 represents the first nearest neighbor symbol corresponding to the first position index, m 2 represents the second position index, and ⁇ m2 represents the third position index corresponding to the second position index.
  • the calculation module 502 is specifically configured to determine a second relationship parameter based on the encoding flag, and determine a second probability corresponding to the transmission signal based on the second relationship parameter.
  • the calculation module 502 is specifically configured to determine the second relationship parameter according to the second parameter formula, and determine the second probability corresponding to the received signal in the modulation symbol constellation point set according to the second probability formula;
  • the second probability formula is m 1 represents the first position index, ⁇ m1 represents the first nearest neighbor symbol corresponding to the first position index, m 2 represents the second position index, ⁇ m2 represents the second nearest neighbor symbol corresponding to the second position index, Indicates the first target probability corresponding to the received signal in the modulation symbol constellation point set in the case of the first nearest neighbor symbol; Indicates the second target probability corresponding to the received signal in the modulation symbol constellation point set
  • the parallel interference elimination module 503 is specifically configured to determine the estimated value corresponding to the transmitted signal according to the estimation formula; the estimation formula is: represents the estimated value, m 1 represents the first position index, ⁇ m1 represents the first nearest neighbor symbol corresponding to the first position index, m 2 represents the second position index, and ⁇ m2 represents the second nearest neighbor symbol corresponding to the second position index.
  • neighbor symbol represents the situation in which the first nearest neighbor symbol , the first target probability corresponding to the received signal in the modulation symbol constellation point set, Indicates the second target probability corresponding to the received signal in the modulation symbol constellation point set in the case of the second nearest neighbor symbol.
  • Figure 6 illustrates a schematic diagram of the physical structure of an electronic device.
  • the electronic device may include: a processor (Processor) 610, a communication interface (Communications Interface) 620, a memory (Memory) 630 and a communication bus 640.
  • the processor 610, the communication interface 620, and the memory 630 complete communication with each other through the communication bus 640.
  • the processor 610 may include a selector 6101, a calculator 6102 and a parallel interference canceller 6103.
  • the processor 610 may call logical instructions in the memory 630 to execute a signal detection method, which method includes: in the process of detecting the transmission signal of the terminal device , the target symbol parameters corresponding to the received signal are determined; based on the target symbol parameters, the probability corresponding to the received signal in the modulation symbol constellation point set is determined; based on the probability, the estimated value corresponding to the transmitted signal is determined.
  • the above-mentioned logical instructions in the memory 630 can be implemented in the form of software functional units and can be stored in a computer-readable storage medium when sold or used as an independent product.
  • the technical solution of the present disclosure is essentially or the part that contributes to the relevant technology or the part of the technical solution can be embodied in the form of a software product.
  • the computer software product is stored in a storage medium and includes several The instructions are used to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present disclosure.
  • the aforementioned storage media include: U disk, mobile hard disk, read-only memory (ROM), random access memory (Random Access Memory, RAM), magnetic disk or optical disk and other media that can store program code. .
  • the present disclosure also provides a computer program product.
  • the computer program product includes a computer program.
  • the computer program can be stored on a non-transitory computer-readable storage medium.
  • the computer can Executing the signal detection method provided by each of the above methods, the method includes: in the process of detecting the transmission signal of the terminal device, determining the target symbol parameters corresponding to the received signal; according to the target symbol parameters, determining the modulation symbol constellation point of the received signal The corresponding probability in the set; based on this probability, the estimated value corresponding to the sent signal is determined.
  • the present disclosure also provides a non-transitory computer-readable storage medium on which a computer program is stored.
  • the computer program is implemented when executed by a processor to perform the signal detection method provided by each of the above methods.
  • the method includes: In the process of detecting the transmission signal of the terminal device, the target symbol parameters corresponding to the received signal are determined; according to the target symbol parameters, the probability corresponding to the received signal in the modulation symbol constellation point set is determined; based on the probability, the corresponding symbol of the transmitted signal is determined estimated value.
  • the device embodiments described above are merely illustrative, in which the units described as separate components may be Alternatively, it may not be physically separate.
  • the components shown as units may or may not be physical units, that is, they may be located in one place, or they may be distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. Persons of ordinary skill in the art can understand and implement the method without any creative effort.
  • each embodiment can be implemented by software plus a necessary general hardware platform, and of course, it can also be implemented by hardware.
  • the computer software products can be stored in computer-readable storage media, such as ROM/RAM, disks. , optical disk, etc., including a number of instructions to cause a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in various embodiments or certain parts of the embodiments.

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Abstract

本公开提供一种信号检测方法、装置、电子设备及存储介质，应用于通信技术领域，该方法包括：在检测终端设备的传输信号的过程中，确定接收信号对应的目标符号参数；根据该目标符号参数，确定该接收信号在调制符号星座点集合中对应的概率；基于该概率，确定发送信号对应的估计值。

Description

信号检测方法、装置、电子设备及存储介质
相关申请的交叉引用
本公开要求于2022年06月07日提交的申请号为2022106421013，发明名称为“信号检测方法、装置、电子设备及存储介质”的中国专利申请的优先权，其通过引用方式全部并入本文。
技术领域
本公开涉及通信技术领域，尤其涉及一种信号检测方法、装置、电子设备及存储介质。
背景技术
相关技术中，终端设备中的数字信号处理器(Digital Signal Processer，DSP)一般采用大规模多输入多输出(Massive-Multiple Input Multiple Output，M-MIMO)检测算法对该终端设备的传输信号进行检测。该M-MIMO检测算法可以包括但不限于最大似然(Maximum Likelihood，ML)算法、最大后验(Maximum A Posterior，MAP)算法、基于贝叶斯推理的消息传递类检测(Message Passing Detection，MPD)算法。
然后，无论终端设备是利用ML算法、MAP算法，还是利用基于贝叶斯推理的MPD算法对该终端设备的传输信号进行检测，都使得该数字信号处理器的硬件实现度较难，整个信号检测过程较为复杂，从而无法准确检测该终端设备的传输信号。
发明内容
本公开提供一种信号检测方法、装置、电子设备及存储介质，用以解决相关技术中终端设备利用M-MIMO检测算法对该终端设备的传输信号进行检测，由于整个信号检测过程较为复杂，导致对信号进行准确检测时所对应的检测硬件代价较大，本公开通过低复杂度设计思想设计出较为简化的信号检测装置，该信号检测装置可以包括选择器、计算器和并行干扰消除器，这样即可对终端设备中的信号实现低复杂度且高准确度地检测。
本公开提供一种信号检测方法，包括：
在检测终端设备的传输信号的过程中，确定接收信号对应的目标符号参数；
根据该目标符号参数，确定该接收信号在调制符号星座点集合中对应的概率；
基于该概率，确定发送信号对应的估计值。
本公开还提供一种信号检测装置，包括：
选择模块，设置为在检测终端设备的传输信号的过程中，确定接收信号对应的目标符号参数；
计算模块，设置为根据该目标符号参数，确定该接收信号在调制符号星座点集合中对应的概率；
并行干扰消除模块，设置为基于该概率，确定发送信号对应的估计值。
本公开还提供一种电子设备，包括存储器、处理器及存储在存储器上并可在处理器上运行的计算机程序，所述处理器包括选择器、计算器和并行干扰消除器，所述处理器执行所述程序时实现如上述任一种所述信号检测方法。
本公开还提供一种非暂态计算机可读存储介质，其上存储有计算机程序，该计算机程序被处理器执行时实现如上述任一种所述信号检测方法。
本公开还提供一种计算机程序产品，包括计算机程序，所述计算机程序被处理器执行时实现如上述任一种所述信号检测方法。
本公开提供的信号检测方法、装置、电子设备及存储介质，通过在检测终端设备的传输信号的过程中，确定接收信号对应的目标符号参数；根据该目标符号参数，确定该接收信号在调制符号星座点集合中对应的概率；基于该概率，确定发送信号对应的估计值。上述方法用以解决相关技术中终端设备利用M-MIMO检测算法对该终端设备的传输信号进行检测，由于整个信号检测过程较为复杂，从而导致对信号进行准确检测时所对应的检测硬件代价较大，本公开通过低复杂度设计思想设计出较为简化的信号检测装置，该信号检测装置包括选择器、计算器和并行干扰消除器，这样即可对终端设备中的信号实现低复杂度且高准确度地检测。
附图说明
为了更清楚地说明本公开实施例或相关技术中的技术方案，下面将对实施例或相关技术描述中所需要使用的附图作一简单地介绍，显而易见地，下面描述中的附图是本公开的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1a是本公开提供的信号检测装置的结构示意图之一；
图1b是本公开提供的星座处理元件的结构示意图；
图1c是本公开提供的并行干扰消除器的结构示意图；
图2是本公开提供的信号检测方法的流程示意图之一；
图3a是本公开提供的信号检测方法的流程示意图之二；
图3b是本公开提供的信号检测方法对应的性能仿真示意图之一；
图3c是本公开提供的信号检测方法对应的性能仿真示意图之二；
图3d是本公开提供的信号检测方法对应的性能仿真示意图之三；
图4a是本公开提供的信号检测方法的流程示意图之三；
图4b是本公开提供的仿真结果示意图；
图5是本公开提供的信号检测装置的结构示意图之二；
图6是本公开提供的电子设备的结构示意图。
具体实施方式
为使本公开的目的、技术方案和优点更加清楚，下面将结合本公开中的附图，对本公开中的技术方案进行清楚、完整地描述，显然，所描述的实施例是本公开一部分实施例，而不是全部的实施例。基于本公开中的实施例，本领域普通技术人员在没有作出创造性劳动前提下所获得的所有其他实施例，都属于本公开保护的范围。
在相关技术中，MPD算法可以包括但不限于：置信度传播(Belief Propagation，BP)信号检测算法、信道硬化辅助的消息传递(Channel Hardening-Exploiting Message Passing，CHEMP)信号检测算法及近似消息传递(Approximate Message Passing，AMP)信号检测算法等。
AMP信号检测算法最早用于解决最小绝对收缩和选择算子(Least Absolute Shrinkage and Selection Operator，LASSO)问题，此外，还可用于解决稀疏信号恢复和压缩感知问题。终端设备在利用AMP信号检测算法对该终端设备的传输信号进行检测时，由于无法准确计算矩匹配，所以，导致该终端设备无法准确检测传输信息。
如图1a所示，是本公开提供的信号检测装置的结构示意图。在图1a中，信号检测装置10包括：控制器单元(Control Unit，CU)101、迭代单元102及寄存器单元103。
控制器单元101，设置为控制时钟和输入/输出(Input/Output，I/O)；
迭代单元102，设置为确定接收信号在每次迭代更新时所对应的目标符号参数、在调制符号星座点集合中对应的概率及发送信号对应的估计值；
寄存器单元103，设置为存储I/O和辅助数据，该辅助数据可以包括但不限于上述目 标符号参数、概率及估计值。
其中，迭代单元102可以包括：星座处理元件1021和并行干扰消除元件1022。星座处理元件1021的数量为p个，并行干扰消除元件1022的数量为q个。示例性的，p的取值为4，分别为为第一星座处理元件、第二星座处理元件、第三星座处理元件和第四星座处理元件，q的取值为4，分别为为第一并行干扰消除元件、第二并行干扰消除元件、第三并行干扰消除元件和第四并行干扰消除元件。
寄存器单元103可以包括：只读存储器(Read Only Memory，ROM)，寄存器单元103的数量为s个，s的取值为4，分别为第一寄存器单元、第二寄存器单元、第三寄存器单元和第四寄存器单元，第一寄存器单元设置为存储匹配滤波输入，第二寄存器单元设置为存储信道矩阵，第三寄存器单元设置为存储输出结果，第四寄存器单元设置为存储辅助数据。
并行干扰消除元件1022可以包括：计算器和并行干扰消除器，计算器设置为确定接收信号对应的概率，并行干扰消除器设置为确定发送信号对应的估计值。可选的，计算器可以包括：数值变化选择器和段移选择器。
在一些实施例中，如图1b所示，是本公开提供的星座处理元件的结构示意图。在图1b中，星座处理元件1021包括最近邻近似(Nearest Neighbor Approximation，NNA)选择器(简称：选择器)、加法器、乘法器和选择加法器，选择器设置为确定接收信号对应的目标符号参数，加法器设置为加法运算，乘法器设置为乘法运算，选择加法器设置为选择数据后进行加法运算；其中，加法器与NNA选择器和乘法器连接，NNA选择器和乘法器与第一流水寄存器连接，第一流水寄存器与选择加法器连接，选择加法器与第二流水寄存器连接。可选的，NNA选择器可包括多路选择器(Multiplexer，MUX)-Δ和MUX-Ω：
在一些实施例中，如图1c所示，是本公开提供的并行干扰消除器的结构示意图。在图1c中，并行干扰消除器可以包括均值选择器和矩阵向量乘器，均值选择器设置为对数据进行移位加支路选择。
本公开实施例涉及的信号检测装置可以利用NNA-AMP算法和硬件友好型(Hardware-Friendly AMP，HF-AMP)信号检测算法，对终端设备的接收信号进行检测。
本公开实施例涉及的终端设备可以包括但不限于：移动终端、可穿戴设备及电脑等。该终端设备中可以设有窄带大规模多输入多输出M-MIMO装置。
其中，该M-MIMO装置可包括Nt个发射天线和Nr个接收天线，Nt≥2，Nr≥2，Nt<Nr。
在一些实施例中，对终端设备的接收信号进行调制的方式包括调制符号星座点集合 (简称：星座点集)为Ω的Q种符号正交幅度调制(Q-Quadrature Amplitude Modulation，Q-QAM)方式。
在Q-QAM方式下，上述M-MIMO装置对应的复数信号传输模型为
其中，表示该终端设备的的无线通信信道对应的传输矩阵，表示接收天线对应的接收信号向量，表示发射天线对应的发送信号向量，表示噪声向量。
示例性的，假设独立分布瑞利信道，n对应的均值为0，n对应的噪声方差为1/Nr，此时，表示加性高斯白噪声(Additive White Gaussian Noise，AWGN)向量， 对应的均值为0，对应的噪声方差为 表示单位矩阵。
可选的，Q种符号中Q的取值可以为16、32、64及256中的其中一种，此处不作具体限定。
在一些实施例中，终端设备中的信道状态信息(Channel State Information，CSI)包括信道矩阵H，假设CSI是已知的，即H已知的，那么，该终端设备可将上述复数信号传输模型转换为等效实数模型：y＝Hx+n。
其中，H表示终端设备的无线通信信道对应的传输矩阵，该传输矩阵的维度为2Nr×2Nt，H∈R2Nr×2Nt，H与本公开实施例涉及的相应算法是对应的；y＝[y1，y2，…，y2Nr]T，表示接收信号矢量，y∈R2Nr×1；[.]T表示转置操作；x＝[x1，x2，…，x2Nt]T，表示发送信号矢量，x∈Ω2Nt×1，Ω表示Q-QAM星座中实部/虚部对应的实数集合，该实数集合的大小为n＝[n1，n2，…，n2Nr]T，表示AWGN矢量，n对应的均值为0，n对应的噪声方差为σn 2。
需要说明的是，本公开实施例涉及的执行主体可以是信号检测装置，也可以是终端设备。下面以终端设备为例，对本公开实施例进行进一步地说明。
如图2所示，是本公开提供的信号检测方法的流程示意图，可以包括：
201、在检测终端设备的传输信号的过程中，确定接收信号对应的目标符号参数。
可选的，目标符号参数可以包括：调制符号星座点集合中的最近邻符号ω，或，该对应的编码标志F。
终端设备在检测该终端设备的接收信号y的过程中，可以利用选择器从寄存器单元的辅助数据包括的中，确定ω；也可以根据该对应的位置索引m，确定该对应的 编码标志，此处不作具体限定。
在一些实施例中，终端设备可以根据第一预设数量的位置索引m，在中确定该m对应的最近邻符号ω，该ω的数量与该m的数量相同；也可以根据该第一预设数量的m对进行划分，得到第二预设数量的区间，并将这第二预设数量的区间分别用相应的格雷编码进行标记，得到第二预设数量的编码标志F，此处不作具体限定。
其中，第一预设数量和第二预设数量可以相同，也可以不同，该第一预设数量和该第二预设数量可以是终端设备出厂前设置的，也可以是用户根据实际需求自定义的，此处不作具体限定。
202、根据目标符号参数，确定接收信号在调制符号星座点集合中对应的概率。
在一些实施例中，终端设备可根据目标符号参数，先确定接收信号对应的关系参数，再根据该关系参数，确定该接收信号在调制符号星座点集合中对应的概率。
在一些实施例中，终端设备可以根据上述ω，确定接收信号对应的第一概率，也可以根据上述F，确定该接收信号对应的第二概率，此处不作具体限定。
也就是说，终端设备可以根据ω对应的第一关系参数，确定接收信号在调制符号星座点集合中对应的第一概率，也可以根据F对应的第二关系参数，确定该接收信号在该调制符号星座点集合中对应的第二概率，此处不作具体限定。
可选的，在步骤202之前，该方法还可以包括：终端设备利用控制器单元根据获取的该终端设备的发送信号、接收信号、信道状态信息CSI和噪声信息，分别得到发送信号矢量x、接收信号矢量y、信道矩阵H和噪声方差σn 2。然后，该终端设备根据x、y、H和σn 2，得到格拉姆(Gram)信道矩阵G及H对应的匹配滤波后接收信号b。其中，G＝HTH，b＝HTy。
最后，该终端设备利用G及b，可以确定接收信号对应的概率。
203、基于概率，确定发送信号对应的估计值。
在一些实施例中，终端设备可以基于概率，确定发送信号对应的检测误差，再根据该检测误差，确定该发送信号对应的估计值。
在一些实施例中，终端设备可以基于概率，先确定接收信号对应的均值，再基于该均值，确定该接收信号对应的检测误差。
可选的，检测误差可以是终端设备利用并行干扰消除器中的均值选择器得到的。终端设备利用第一加法器将加法树的输出与滤波后接收信号bi组合，以得到检测误差。
可选的，估计值可以是终端设备利用并行干扰消除器中的矩阵向量乘器得到的。 在该矩阵向量乘器中，终端设备可以将gi＝[gi,1，gi,2，…，gi,2Nt]T分别与进行内积，每组由乘法器和五级加法树执行，以实现G与的乘法计算。其中，gi表示G中的第i行元素。
在本公开实施例中，上述方法用以解决相关技术中终端设备利用M-MIMO检测算法对该终端设备的传输信号进行检测，由于整个信号检测过程较为复杂，从而导致对信号进行准确检测时所对应的检测硬件代价较大，本公开通过低复杂度设计思想设计出较为简化的信号检测装置，该信号检测装置可以包括选择器、计算器和并行干扰消除器，这样即可对终端设备中的信号实现低复杂度且高准确度地检测。
如图3a所示，是本公开提供的信号检测方法的流程示意图，可以包括：
301、在检测终端设备的传输信号的过程中，在调制符号星座点集合中，确定接收信号对应的最近邻符号。
终端设备在该检测终端设备的传输信号的过程中，可以利用选择器根据第一预设数量的位置索引m，在调制符号星座点集合中，确定该m对应的最近邻符号ω。
示例性的，第一预设数量为2。终端设备可以根据2个位置索引，分别为第一位置索引m1和第二位置索引m2，在中确定该m1对应的第一最近邻符号ωm1，并确定该m2对应的第二最近邻符号ωm2。
其中，m1和m2是终端设备随机抽取的。
302、根据最近邻符号，确定第一关系参数，并根据第一关系参数，确定接收信号在调制符号星座点集合中对应的第一概率。
在一些实施例中，终端设备对应的信号流图(Signal Flow Graph，SFG)中存在大量的处理节点。该终端设备可以先从该SFG中删除部分性能依赖性低的处理节点，以达到压缩处理节点的目的，从提高其它处理节点的处理效率。
此时，该终端设备可以根据动态公式得到该终端设备对应的噪声方差τ(l)。但由于该终端设备中M-MIMO装置对应的传输模型的β因子较小，所以，是可以忽略不计的。然后，该终端设备可以将该动态公式可以简化为静态公式τ(l)＝σn，从而得到较为准确的噪声方差τ(l)。
可选的，终端设备根据最近邻符号，确定第一关系参数，并根据第一关系参数，确定接收信号在调制符号星座点集合中对应的第一概率，可以包括：终端设备根据第一参数公式，确定第一关系参数，并根据第一概率公式，确定接收信号在调制符号星座点集合中对 应的第一概率。
其中，第一参数公式为l表示迭代次数，表示第一关系参数，sω＝ωm2-ωm1表示第二最近邻符号与第一最近邻符号之差，aω＝ωm2+ωm1表示第二最近邻符号与第一最近邻符号之和，表示终端设备对应的归一化参数；
第一概率公式为m表示位置索引，表示第一概率；表示在位置索引为第一最近邻符号的情况下，接收信号在调制符号星座点集合中对应的概率。
在一些实施例中，上述第一参数公式中的-|·|可以是终端设备利用计算器中的数值变化选择器得到的，可以是终端设备利用计算器中的段移选择器得到的。
在一些实施例中，终端设备为了简化上述第一参数公式和第一概率公式中含有的除法和指数等非线性计算部分所带来的计算复杂度，该终端设备可以对该非线性计算部分进行分片线性逼近(Piecewise Linear Approximation，PLA)，使得该终端设备将一些数据在有限的数值区间内将非线性部分适当地向线性部分逼近，以减小计算器的计算性能损失，提高计算结果的准确性。
在上述第一参数公式中，非线性函数为终端设备可以先将τ(l)裁剪在[ηa,1，ηb,1]范围内，ηa,1表示第一噪声阈值，ηb,1表示第二噪声阈值；然后，该终端设备利用具有Nseg， 1段的分段线性插值函数来近似该非线性函数为Nseg，1表示第一数量。
在上述第一概率公式中，非线性函数为其中，当的取值足够小时，可以约等于0。终端设备可以先将裁剪在[ηa,2，ηb,2]范围内，ηa,2 表示第三噪声阈值，ηb,2表示第四噪声阈值，ηb,2的取值为0；然后，该终端设备利用具有Nseg，2段的分段线性函数来近似Nseg，2表示第二数量。也就是说，该终端设备利用线性插值函数来代替非线性函数
示例性的，如图3b所示，是本公开提供的信号检测方法对应的性能仿真示意图。在图3b中，方框连接的曲线为处理节点删除前，Nt＝8、Nt＝16和Nt＝32分别对应的比特出错概率(Bit Error Ratio，BER)变化曲线；三角形连接的曲线为处理节点删除后，Nt＝8、Nt＝16和Nt＝32分别对应的BER变化曲线。其中，Es表示接收信号对应符号具有的平均能量，N0表示终端设备对应的信道噪声功率。
通过两条BER变化曲线的对比，在Nt＝8和Nt＝16时，终端设备利用线性插值函数来代替非线性函数后得到的结果对应的BER较小。
示例性的，如图3c所示，是本公开提供的信号检测方法对应的性能仿真示意图。图3c为不同的分别对应的BER变化曲线。在图3c中，在ηa,1＝1/8，ηb,1＝15/8及Nseg，1＝1时，终端设备利用线性插值函数来代替非线性函数后得到的结果对应的BER较小。
如图3d所示，是本公开提供的信号检测方法对应的性能仿真示意图。在图3d中，在ηa,2＝-4，ηb,2＝0及Nseg，2＝1时，终端设备利用线性插值函数来代替非线性函数后得到的结果对应的BER较小。
在一些实施例中，终端设备可以将上述所有可能涉及到的值都存储在寄存器单元的查找表(Look Up Table，LUT)中。可选的，终端设备可以将上述所有可能涉及到的值都存储在PLA中，PLA只需要存储间隔、斜率和截距。在这种情况下，终端设备中存储的数据的数量显著减少，这样可以有效地增加存储空间。终端设备基于PLA得到相应数据的方法与传统的坐标旋转数字计算(Coordinate Rotation Digital Computer，CORDIC)算法相比，可以在一定程度上减小整个计算过程的处理时延，即可以再一定程度上减小乘法器和加法器的处理时间。
303、根据估计公式，确定发送信号对应的估计值。
其中，估计公式为 表示估计值，m1表示第一位置索引，ωm1表示第一位置索引对应的第一最近邻符号，m2表示第二位置索引，ωm2表 示第二位置索引对应的第二最近邻符号，表示在第一最近邻符号的情况下，接收信号在调制符号星座点集合中对应的第一目标概率，表示在第二最近邻符号的情况下，接收信号在调制符号星座点集合中对应的第二目标概率。
可选的，步骤303之后，该方法还可以包括：终端设备发送信号对应的估计值，确定该发送信号与输出信号之间的检测误差。
可选的，终端设备发送信号对应的估计值，确定该发送信号与输出信号之间的检测误差，可以包括：终端设备根据误差公式，确定该发送信号与输出信号之间的检测误差。
其中，误差公式为l表示迭代次数；表示检测误差，bi表示终端设备的信道矩阵对应的匹配滤波后接收信号中第i个接收信号，gi,j表示终端设备的格拉姆信道矩阵G中第(i，j)个元素，G＝HTH，H表示终端设备的无线通信信道对应的传输矩阵，表示第j个发送信号对应的估计值。
可以理解的是，由于电子设备获取的估计值是较为准确的，所以，该电子设备根据该估计值确定的发送信号与输出信号之间的检测误差也是较小的。
在本公开实施例中，终端设备可以利用NNA-AMP算法对终端设备的传输信号进行检测。上述方法用以解决相关技术中终端设备利用M-MIMO检测算法对该终端设备的传输信号进行检测，由于整个信号检测过程较为复杂，从而导致对信号进行准确检测时所对应的检测硬件代价较大，本公开通过低复杂度设计思想设计出较为简化的信号检测装置，该信号检测装置可以包括选择器、计算器和并行干扰消除器，这样即可对终端设备中的信号实现低复杂度且高准确度地检测。
如图4a所示，是本公开提供的信号检测方法的流程示意图，可以包括：
401、在检测终端设备的传输信号的过程中，根据调制符号星座点集合对应的位置索引，确定接收信号在调制符号星座点集合中对应的编码标志。
终端设备在该检测终端设备的接收信号的过程中，可以利用选择器根据第一预设数量的位置索引m对进行划分，得到第二预设数量的区间，并将这第二预设数量的区间分别用相应的格雷编码进行标记，得到第二预设数量的编码标志F。
示例性的，第一预设数量为2，第二预设数量为6。终端设备可以根据m1和m2将划分为6个区间，分别为(-∞，-2]、(-2，-1]、(-1，0]、(0，1]、(1，2]及(2，+∞)；然后，该终端设备对这6个区间用相应的格雷编码进行标记，得到6个的编码标志F分别 为F1、F2、F3、F4、F5及F6。
可选的，{F4，F5}可以是选择器包括的MUX-Δ得到的，{F1，F2，F3}可以是选择器包括的MUX-Ω选择器得到的。
402、根据编码标志，确定第二关系参数，并根据第二关系参数，确定发送信号在调制符号星座点集合中对应的第二概率。
可选的，终端设备可以基于上述6个区间，可以计算出aω和sω。
其中，aω在不同的区间会存在3个可能的值，分别为-4、0和4，终端设备可以确定aω对应的编码标志{F4，F5}，而{F4，F5}对应的格雷编码分别为01、11和10；sω在不同的区间会存在2个可能的值，分别为-2和2，终端设备可以确定sω对应的编码标志{F6}，而{F6}对应的格雷编码分别为0和1。因此，终端设备可以将步骤302中的第一参数公式化简为第二参数公式。
在一些实施例中，由于终端身边已经利用线性插值函数来代替非线性函数，所以，该终端设备可以将第一参数公式简化为第二参数公式，可以将第一概率公式简化为第二概率公式。
可选的，终端设备根据编码标志，确定第二关系参数，并根据第二关系参数，确定发送信号在调制符号星座点集合中对应的第二概率，可以包括：终端设备根据第二参数公式，确定第二关系参数，并根据第二概率公式，确定接收信号在调制符号星座点集合中对应的第二概率。
其中，第二参数公式为l表示迭代次数，表示第二关系参数，表示该终端设备对应的归一化参数，τ(l)＝σn 2表示终端设备对应的噪声方差，F4表示第一编码标志，F5表示第二编码标志；
第二概率公式为
表示在第一最近邻符号的情况下，接收信号在调制符号星座点集合中对应的第一目标概率；表示在第二最近邻符号的情况下，接收信号在调制符号星座 点集合中对应的第二目标概率。
可选的，和可以是终端设备利用计算器中的绝对值+计算器得到的。
示例性的，终端设备将线性插值函数中的量化斜率取值为0.5，将量化截距取值为-0.125。
此时，
403、根据估计公式，确定发送信号对应的估计值。
需要说明的是，步骤403中终端设备根据估计公式，确定发送信号对应的估计值的过程与图3所示步骤303终端设备根据估计公式，确定发送信号对应的估计值的过程类似，此处不作具体赘述。
由于步骤302中的第一关系参数与sω无关，所以，终端设备在化简第一参数公式的过程中，不需要编码标志{F6}。那么，该终端设备在利用并行干扰消除器确定发送信号对应的估计值时，可以通过子表达式共享将整数化星座的乘法操作简化为移位和加法(Shift And Adder，SAA)操作。
示例性的，电子设备可以通过子表达式共享将简化为均值表。
均值表如下：
可选的，步骤303之后，该方法还可以包括：终端设备基于概率，确定接收信号对应 的均值，并根据均值，确定发送信号与接收信号之间的检测误差。
可选的，终端设备基于概率，确定接收信号对应的均值，并根据均值，确定发送信号与接收信号之间的检测误差，可以包括：终端设备根据均值表，计算得到接收信号对应的均值，并根据均值，确定发送信号与接收信号之间的检测误差。
也就是说，终端设备利用并行干扰消除器基于不同的{F1，F2，F3}，得到的均值也是不同的，然后，该终端设备再根据该均值，可准确确定接收信号对应的检测误差。
可以理解的是，由于电子设备获取的估计值是较为准确的，所以，该电子设备根据该估计值确定的发送信号与输出信号之间的检测误差也是较小的。
在一些实施例中，当M-MIMO装置中Nr＝8，Nt＝128时，终端设备的接收信号对应的调制方式为16-QAM。通过仿真验证，终端设备利用AMP算法、NAA-AMP算法和HF-AMP算法在检测接收信号的过程中，每个算法在不同迭代次数下，终端设备的性能参数基本一致，且在迭代次数L-4时收敛，实现了提高传输信息检测的准确性。其中，AMP算法可以集成在AMP检测器上，HF-AMP算法可以集成在HF-AMP检测器上，HF-AMP算法可以集成在HF-AMP检测器上。
其次，终端设备需要对所有涉及的变量进行量化：如图4b所示，是本公开提供的仿真结果示意图。在图4b中，具有4位小数和5位小数部分位宽的HF-AMP遭受严重的性能劣化。具有6位小数部分位宽的HF-AMP几乎可以完美地恢复浮点HF-AMP的性能。因此，HF-AMP的量化方案取为1-6-6。
最后进一步完成基于现场可编辑逻辑门阵列(Filed Programmable Gate Array，FPGA)的硬件实现与验证。使用Xilinx Virtex-7Ultrascale vu440-flga2892-2-e FPGA实现了量化的HF-AMP算法。
最后，进行芯片级的专用集成电路(Application Specific Integrated Circuit，ASIC)实现，HF-AMP检测器采用SMIC 65nm LL 1P9M CMOS技术实现接收信号的检测，HF-AMP检测器在Synopsys公司的设计编译(Design Compile)软件上综合，结果使用该Synopsys公司设计流程指导(IC Compiler)软件进行布局和布线。门级网表的注释翻转率被转换为环境(Prime-Time)PX的开关活动交换格式(Switching Activity Interchange Format，SAIF)，以测量基于时间的纯芯片功耗。
进一步地，最终HF-AMP检测器对应的硬件实现了在330MHz时钟下的10.56Gb/s的高吞吐率，基本达到了业界最高水平，同时，保证了整体功耗为103.76mW。在5.03的高吞吐面积比的情况下，确保了单位比特能耗为9.83pJ/b，实现了高效的硬件架构，具有绿 色节能的未来前景。
在本公开实施例中，终端设备可以利用HF-AMP信号检测算法，对终端设备的传输信号进行检测。上述方法用以解决相关技术中终端设备利用M-MIMO检测算法对该终端设备的传输信号进行检测，由于整个信号检测过程较为复杂，从而导致对信号进行准确检测时所对应的检测硬件代价较大，本公开通过低复杂度设计思想设计出较为简化的信号检测装置，该信号检测装置包括选择器、计算器和并行干扰消除器，即可对终端设备中的信号实现低复杂度且高准确度地检测。
下面对本公开提供的信号检测装置进行描述，下文描述的信号检测装置与上文描述的信号检测方法可相互对应参照。
如图5所示，是本公开提供的信号检测装置的结构示意图，可以包括：
选择模块501，设置为在检测终端设备的传输信号的过程中，确定接收信号对应的目标符号参数；
计算模块502，设置为根据该目标符号参数，确定该接收信号在调制符号星座点集合中对应的概率；
并行干扰消除模块503，设置为基于该概率，确定发送信号对应的估计值。
可选的，选择模块501，具体设置为在该调制符号星座点集合中，确定接收信号对应的最近邻符号；或，根据该调制符号星座点集合对应的位置索引，确定该接收信号在该调制符星座点集合号中对应的编码标志。
可选的，计算模块502，具体设置为根据该最近邻符号，确定第一关系参数，并根据该第一关系参数，确定该接收信号在调制符号星座点集合中对应的第一概率。
可选的，计算模块502，具体设置为根据第一参数公式，确定第一关系参数，并根据第一概率公式，确定该接收信号在调制符号星座点集合中对应的第一概率；该第一参数公式为l表示迭代次数，表示该第一关系参数，m1表示第一位置索引，ωm1表示该第一位置索引对应的第一最近邻符号，m2表示第二位置索引，ωm2表示该第二位置索引对应的第二最近邻符号；sω＝ωm2-ωm1表示该第二最近邻符号与该第一最近邻符号之差，aω＝ωm2+ωm1表示该第二最近邻符号与该第一最近邻符号之和，τ(l)＝σn 2表示该终端设备中信道矩阵对应的噪声方差，表示该终端设备对应的归一化参数，表示该调制符号星座点集合；该第一概率公式为 m表示位置索引，表示该第一概率；表示在该位置索引为该第一最近邻符号的情况下，该接收信号在该调制符号星座点集合中对应的概率。
可选的，计算模块502，具体设置为根据该编码标志，确定第二关系参数，并根据该第二关系参数，确定该传输信号对应的第二概率。
可选的，计算模块502，具体设置为根据第二参数公式，确定第二关系参数，并根据第二概率公式，确定该接收信号在调制符号星座点集合中对应的第二概率；该第二参数公式为l表示迭代次数，表示该第二关系参数，表示该终端设备对应的归一化参数，表示该调制符号星座点集合，τ(l)＝σn 2表示该终端设备中信道矩阵对应的噪声方差，F4表示第一编码标志，F5表示第二编码标志；该第二概率公式为m1表示第一位置索引，ωm1表示该第一位置索引对应的第一最近邻符号，m2表示第二位置索引，ωm2表示该第二位置索引对应的第二最近邻符号，表示在该第一最近邻符号的情况下，该接收信号在该调制符号星座点集合中对应的第一目标概率；表示在该第二最近邻符号的情况下，该接收信号在该调制符号星座点集合中对应的第二目标概率。
可选的，并行干扰消除模块503，具体设置为根据估计公式，确定发送信号对应的估计值；该估计公式为 表示该估计值，m1表示第一位置索引，ωm1表示该第一位置索引对应的第一最近邻符号，m2表示第二位置索引，ωm2表示该第二位置索引对应的第二最近邻符号，表示在该第一最近邻符号的情况 下，该接收信号在该调制符号星座点集合中对应的第一目标概率，表示在该第二最近邻符号的情况下，该接收信号在该调制符号星座点集合中对应的第二目标概率。
图6示例了一种电子设备的实体结构示意图，如图6所示，该电子设备可以包括：处理器(Processor)610、通信接口(Communications Interface)620、存储器(Memory)630和通信总线640，其中，处理器610，通信接口620，存储器630通过通信总线640完成相互间的通信。处理器610可以包括选择器6101、计算器6102和并行干扰消除器6103，处理器610可以调用存储器630中的逻辑指令，以执行信号检测方法，该方法包括：在检测终端设备的传输信号的过程中，确定接收信号对应的目标符号参数；根据该目标符号参数，确定该接收信号在调制符号星座点集合中对应的概率；基于该概率，确定发送信号对应的估计值。
此外，上述的存储器630中的逻辑指令可以通过软件功能单元的形式实现并作为独立的产品销售或使用时，可以存储在一个计算机可读取存储介质中。基于这样的理解，本公开的技术方案本质上或者说对相关技术做出贡献的部分或者该技术方案的部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)执行本公开各个实施例所述方法的全部或部分步骤。而前述的存储介质包括：U盘、移动硬盘、只读存储器(Read-Only Memory，ROM)、随机存取存储器(Random Access Memory，RAM)、磁碟或者光盘等各种可以存储程序代码的介质。
另一方面，本公开还提供一种计算机程序产品，所述计算机程序产品包括计算机程序，计算机程序可存储在非暂态计算机可读存储介质上，所述计算机程序被处理器执行时，计算机能够执行上述各方法所提供的信号检测方法，该方法包括：在检测终端设备的传输信号的过程中，确定接收信号对应的目标符号参数；根据该目标符号参数，确定该接收信号在调制符号星座点集合中对应的概率；基于该概率，确定发送信号对应的估计值。
又一方面，本公开还提供一种非暂态计算机可读存储介质，其上存储有计算机程序，该计算机程序被处理器执行时实现以执行上述各方法提供的信号检测方法，该方法包括：在检测终端设备的传输信号的过程中，确定接收信号对应的目标符号参数；根据该目标符号参数，确定该接收信号在调制符号星座点集合中对应的概率；基于该概率，确定发送信号对应的估计值。
以上所描述的装置实施例仅仅是示意性的，其中所述作为分离部件说明的单元可以是 或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部模块来实现本实施例方案的目的。本领域普通技术人员在不付出创造性的劳动的情况下，即可以理解并实施。
通过以上的实施方式的描述，本领域的技术人员可以清楚地了解到各实施方式可借助软件加必需的通用硬件平台的方式来实现，当然也可以通过硬件。基于这样的理解，上述技术方案本质上或者说对相关技术做出贡献的部分可以以软件产品的形式体现出来，该计算机软件产品可以存储在计算机可读存储介质中，如ROM/RAM、磁碟、光盘等，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)执行各个实施例或者实施例的某些部分所述的方法。
最后应说明的是：以上实施例仅用以说明本公开的技术方案，而非对其限制；尽管参照前述实施例对本公开进行了详细的说明，本领域的普通技术人员应当理解：其依然可以对前述各实施例所记载的技术方案进行修改，或者对其中部分技术特征进行等同替换；而这些修改或者替换，并不使相应技术方案的本质脱离本公开各实施例技术方案的精神和范围。

Claims (17)

  1. 一种信号检测方法，其中，包括：
    在检测终端设备的传输信号的过程中，确定接收信号对应的目标符号参数；
    根据所述目标符号参数，确定所述接收信号在调制符号星座点集合中对应的概率；
    基于所述概率，确定发送信号对应的估计值。
  2. 根据权利要求1所述的信号检测方法，其中，所述确定接收信号对应的目标符号参数，包括：
    在所述调制符号星座点集合中，确定接收信号对应的最近邻符号；
    或，
    根据所述调制符号星座点集合对应的位置索引，确定所述接收信号在所述调制符星座点集合号中对应的编码标志。
  3. 根据权利要求2所述的信号检测方法，其中，在所述在调制符号星座点集合中，确定接收信号对应的最近邻符号的情况下，所述根据所述目标符号参数，确定所述接收信号在调制符号星座点集合中对应的概率，包括：
    根据所述最近邻符号，确定第一关系参数，并根据所述第一关系参数，确定所述接收信号在调制符号星座点集合中对应的第一概率。
  4. 根据权利要求3所述的信号检测方法，其中，所述根据所述最近邻符号，确定第一关系参数，并根据所述第一关系参数，确定所述接收信号在调制符号星座点集合中对应的第一概率，包括：
    根据第一参数公式，确定第一关系参数，并根据第一概率公式，确定所述接收信号在调制符号星座点集合中对应的第一概率；
    所述第一参数公式为
    l表示迭代次数，表示所述第一关系参数，m1表示第一位置索引，ωm1表示所述第一位置索引对应的第一最近邻符号，m2表示第二位置索引，ωm2表示所述第二位置索引对应的第二最近邻符号；sω＝ωm2-ωm1表示所述第二最近邻符号与所述第一最近邻符号之差，aω＝ωm2+ωm1表示所述第二最近邻符号与所述第一最近邻符号之和，τ(l)＝σn 2表示所述终端设备中信道矩阵对应的噪声方差，表示所述终端设备对应的归一化参数，表 示所述调制符号星座点集合；
    所述第一概率公式为m表示位置索引，
    表示所述第一概率；表示在所述位置索引为所述第一最近邻符号的情况下，所述接收信号在所述调制符号星座点集合中对应的概率。
  5. 根据权利要求2所述的信号检测方法，其中，在所述根据所述调制符号星座点集合对应的位置索引，确定所述接收信号在调制符星座点集合号中对应的编码标志的情况下，所述根据所述目标符号参数，确定所述接收信号在调制符号星座点集合中对应的概率，包括：
    根据所述编码标志，确定第二关系参数，并根据所述第二关系参数，确定所述接收信号在调制符号星座点集合中对应的第二概率。
  6. 根据权利要求5所述的信号检测方法，其中，所述根据所述编码标志，确定第二关系参数，并根据所述第二关系参数，确定所述接收信号在调制符号星座点集合中对应的第二概率，包括：
    根据第二参数公式，确定第二关系参数，并根据第二概率公式，确定所述接收信号在调制符号星座点集合中对应的第二概率；
    所述第二参数公式为l表示迭代次数，表示所述第二关系参数，表示所述终端设备对应的归一化参数，表示所述调制符号星座点集合，τ(l)＝σn 2表示所述终端设备中信道矩阵对应的噪声方差，F4表示第一编码标志，F5表示第二编码标志；
    所述第二概率公式为m1表示第一位置索引，ωm1表示 所述第一位置索引对应的第一最近邻符号，m2表示第二位置索引，ωm2表示所述第二位置索引对应的第二最近邻符号；表示在所述第一最近邻符号的情况下，所述接收信号在所述调制符号星座点集合中对应的第一目标概率；表示在所述第二最近邻符号的情况下，所述接收信号在所述调制符号星座点集合中对应的第二目标概率。
  7. 根据权利要求4或6所述的信号检测方法，其中，所述基于所述概率，确定发送信号对应的估计值，包括：
    根据估计公式，确定发送信号对应的估计值；
    所述估计公式为表示所述估计值，m1表示第一位置索引，ωm1表示所述第一位置索引对应的第一最近邻符号，m2表示第二位置索引，ωm2表示所述第二位置索引对应的第二最近邻符号，表示在所述第一最近邻符号的情况下，所述接收信号在所述调制符号星座点集合中对应的第一目标概率，表示在所述第二最近邻符号的情况下，所述接收信号在所述调制符号星座点集合中对应的第二目标概率。
  8. 一种信号检测装置，其中，包括：
    选择模块，设置为在检测终端设备的传输信号的过程中，确定接收信号对应的目标符号参数；
    计算模块，设置为根据所述目标符号参数，确定所述接收信号在调制符号星座点集合中对应的概率；
    并行干扰消除模块，设置为基于所述概率，确定发送信号对应的估计值。
  9. 根据权利要求8所述的信号检测装置，其中，
    所述选择模块，具体设置为在所述调制符号星座点集合中，确定接收信号对应的最近邻符号；或，根据所述调制符号星座点集合对应的位置索引，确定所述接收信号在所述调制符星座点集合号中对应的编码标志。
  10. 根据权利要求9所述的信号检测装置，其中，
    所述计算模块，具体设置为根据所述最近邻符号，确定第一关系参数，并根据所述第一关系参数，确定所述接收信号在调制符号星座点集合中对应的第一概率。
  11. 根据权利要求10所述的信号检测装置，其中，
    所述计算模块，具体设置为根据第一参数公式，确定第一关系参数，并根据第一概率 公式，确定所述接收信号在调制符号星座点集合中对应的第一概率；所述第一参数公式为l表示迭代次数，表示所述第一关系参数，m1表示第一位置索引，ωm1表示所述第一位置索引对应的第一最近邻符号，m2表示第二位置索引，ωm2表示所述第二位置索引对应的第二最近邻符号；
    sω＝ωm2-ωm1表示所述第二最近邻符号与所述第一最近邻符号之差，aω＝ωm2+ωm1表示所述第二最近邻符号与所述第一最近邻符号之和，τ(l)＝σn 2表示所述终端设备中信道矩阵对应的噪声方差，表示所述终端设备对应的归一化参数，表示所述调制符号星座点集合；所述第一概率公式为m表示位置索引，表示所述第一概率；表示在所述位置索引为所述第一最近邻符号的情况下，所述接收信号在所述调制符号星座点集合中对应的概率。
  12. 根据权利要求9所述的信号检测装置，其中，
    所述计算模块，具体设置为根据所述编码标志，确定第二关系参数，并根据所述第二关系参数，确定所述接收信号在调制符号星座点集合中对应的第二概率。
  13. 根据权利要求12所述的信号检测装置，其中，
    所述计算模块，具体设置为根据第二参数公式，确定第二关系参数，并根据第二概率公式，确定所述接收信号在调制符号星座点集合中对应的第二概率；所述第二参数公式为l表示迭代次数，表示所述第二关系参数，表示所述终端设备对应的归一化参数，表示所述调制符号星座点集合，τ(l)＝σn 2表示所述终端设备中信道矩阵对应的噪声方差，F4表示第一编码标志，F5表示第 二编码标志；所述第二概率公式为m1表示第一位置索引，ωm1表示所述第一位置索引对应的第一最近邻符号，m2表示第二位置索引，ωm2表示所述第二位置索引对应的第二最近邻符号；表示在所述第一最近邻符号的情况下，所述接收信号在所述调制符号星座点集合中对应的第一目标概率；表示在所述第二最近邻符号的情况下，所述接收信号在所述调制符号星座点集合中对应的第二目标概率。
  14. 根据权利要求8或10所述的信号检测装置，其中，
    所述并行干扰消除模块，具体设置为根据估计公式，确定发送信号对应的估计值；所述估计公式为表示所述估计值，m1表示第一位置索引，ωm1表示所述第一位置索引对应的第一最近邻符号，m2表示第二位置索引，ωm2表示所述第二位置索引对应的第二最近邻符号，表示在所述第一最近邻符号的情况下，所述接收信号在所述调制符号星座点集合中对应的第一目标概率，表示在所述第二最近邻符号的情况下，所述接收信号在所述调制符号星座点集合中对应的第二目标概率。
  15. 一种电子设备，包括存储器、处理器及存储在所述存储器上并可在所述处理器上运行的计算机程序，其中，所述处理器包括选择器、计算器和并行干扰消除器，所述处理器执行所述程序时实现如权利要求1至7任一项所述信号检测方法。
  16. 一种非暂态计算机可读存储介质，其上存储有计算机程序，其中，所述计算机程序被处理器执行时实现如权利要求1至7任一项所述信号检测方法。
  17. 一种计算机程序产品，其中，包括计算机程序，所述计算机程序被处理器执行时实现如权利要求1至7任一项所述信号检测方法。
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