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CN115037340A - Signal detection method, signal detection device, electronic equipment and storage medium - Google Patents

Signal detection method, signal detection device, electronic equipment and storage medium Download PDF

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Publication number
CN115037340A
CN115037340A CN202210642101.3A CN202210642101A CN115037340A CN 115037340 A CN115037340 A CN 115037340A CN 202210642101 A CN202210642101 A CN 202210642101A CN 115037340 A CN115037340 A CN 115037340A
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probability
determining
received signal
parameter
representing
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CN115037340B (en
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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Zijinshan Laboratory
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Network Communication and Security Zijinshan Laboratory
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Priority to PCT/CN2023/080785 priority patent/WO2023236610A1/en
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    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04BTRANSMISSION
    • H04B7/00Radio transmission systems, i.e. using radiation field
    • H04B7/02Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/0413MIMO systems
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04BTRANSMISSION
    • H04B7/00Radio transmission systems, i.e. using radiation field
    • H04B7/02Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/06Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H04B7/0613Diversity 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
    • H04B7/0615Diversity 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
    • H04B7/0619Diversity 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
    • H04B7/0621Feedback content
    • H04B7/0626Channel coefficients, e.g. channel state information [CSI]
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04BTRANSMISSION
    • H04B7/00Radio transmission systems, i.e. using radiation field
    • H04B7/02Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/06Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H04B7/0613Diversity 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
    • H04B7/0615Diversity 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
    • H04B7/0619Diversity 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
    • H04B7/0621Feedback content
    • H04B7/063Parameters other than those covered in groups H04B7/0623 - H04B7/0634, e.g. channel matrix rank or transmit mode selection
    • YGENERAL 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
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02DCLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00Reducing energy consumption in communication networks
    • Y02D30/70Reducing energy consumption in communication networks in wireless communication networks

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  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Physics & Mathematics (AREA)
  • Mathematical Physics (AREA)
  • Digital Transmission Methods That Use Modulated Carrier Waves (AREA)
  • Radio Transmission System (AREA)

Abstract

The invention provides a signal detection method, a signal detection device, electronic equipment and a storage medium, wherein the method comprises the following steps: determining a target symbol parameter corresponding to a received signal in the process of detecting a transmission signal of terminal equipment; determining the probability of the received signal in the modulation symbol constellation point set according to the target symbol parameter; based on the probability, an estimated value corresponding to the transmission signal is determined. The method is used for solving the problems that in the prior art, the terminal equipment utilizes an M-MIMO detection algorithm to detect the transmission signal of the terminal equipment, and the detection hardware cost corresponding to the accurate detection of the signal is higher due to the fact that the whole signal detection process is complex.

Description

Signal detection method, signal detection device, electronic equipment and storage medium
Technical Field
The present invention relates to the field of communications technologies, and in particular, to a signal detection method and apparatus, an electronic device, and a storage medium.
Background
In the prior art, a Digital Signal Processor (DSP) in a terminal device generally adopts a large-scale Multiple-Input Multiple-Output (M-MIMO) detection algorithm to detect a transmission Signal of the terminal device. The M-MIMO Detection algorithm may include, but is not limited to, a Maximum Likelihood (ML) algorithm, a Maximum A Posteriori (MAP) algorithm, a Message Passing Detection (MPD) algorithm based on bayesian inference.
Then, no matter the terminal device detects the transmission signal of the terminal device by using the ML algorithm, the MAP algorithm or the MPD algorithm based on the bayesian inference, the hardware implementation degree of the digital signal processor is difficult, the whole signal detection process is complicated, and the transmission signal of the terminal device cannot be accurately detected.
Disclosure of Invention
The invention provides a signal detection method, a signal detection device, electronic equipment and a storage medium, which are used for solving the problems that in the prior art, terminal equipment utilizes an M-MIMO detection algorithm to detect a transmission signal of the terminal equipment, and the detection hardware cost corresponding to the accurate detection of the signal is higher due to the fact that the whole signal detection process is complex.
The invention provides a signal detection method, which comprises the following steps:
determining a target symbol parameter corresponding to a received signal in the process of detecting a transmission signal of terminal equipment;
determining the probability of the received signal in the modulation symbol constellation point set according to the target symbol parameter;
based on the probability, an estimated value corresponding to the transmission signal is determined.
The present invention also provides a signal detection apparatus, comprising:
the selection module is used for determining a target symbol parameter corresponding to a received signal in the process of detecting a transmission signal of the terminal equipment;
a calculating module, configured to determine, according to the target symbol parameter, a corresponding probability of the received signal in a modulation symbol constellation point set;
and the parallel interference elimination module is used for determining an estimation value corresponding to the transmission signal based on the probability.
The present invention also provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor comprises a selector, a calculator and a parallel interference canceller, and the processor implements the signal detection method as described in any of the above when executing the program.
The present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements a signal detection method as described in any of the above.
The invention also provides a computer program product comprising a computer program which, when executed by a processor, implements a method of signal detection as described in any one of the above.
The signal detection method, the signal detection device, the electronic equipment and the storage medium provided by the invention determine the target symbol parameter corresponding to the received signal in the process of detecting the transmission signal of the terminal equipment; determining the probability of the received signal in a modulation symbol constellation point set according to the target symbol parameter; based on the probability, an estimated value corresponding to the transmission signal is determined. The method is used for solving the problem that the terminal equipment detects the transmission signal of the terminal equipment by utilizing an M-MIMO detection algorithm in the prior art, and the detection hardware cost corresponding to the accurate detection of the signal is higher due to the fact that the whole signal detection process is complex.
Drawings
In order to more clearly illustrate the technical solutions of the present invention or the prior art, the drawings needed for the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.
FIG. 1a is a schematic structural diagram of a signal detection device provided in the present invention;
FIG. 1b is a schematic diagram of a constellation processing element according to the present invention;
fig. 1c is a schematic structural diagram of a parallel interference canceller provided in the present invention;
FIG. 2 is a schematic flow chart of a signal detection method provided by the present invention;
FIG. 3a is a second schematic flowchart of the signal detection method provided by the present invention;
FIG. 3b is a schematic diagram of a performance simulation corresponding to the signal detection method of the present invention;
FIG. 3c is a second schematic diagram of performance simulation corresponding to the signal detection method of the present invention;
FIG. 3d is a third schematic diagram of performance simulation corresponding to the signal detection method of the present invention;
FIG. 4a is a third schematic flow chart of a signal detection method provided by the present invention;
FIG. 4b is a diagram illustrating simulation results provided by the present invention;
FIG. 5 is a second schematic structural diagram of a signal detection apparatus provided in the present invention;
fig. 6 is a schematic structural diagram of an electronic device provided in the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is obvious that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be obtained by a person skilled in the art without inventive step based on the embodiments of the present invention, are within the scope of protection of the present invention.
In the prior art, MPD algorithms may include, but are not limited to: a Belief Propagation (BP) signal detection algorithm, a Channel Hardening-aided Message Passing (CHEMP) signal detection algorithm, and an Approximate Message Passing (AMP) signal detection algorithm, etc.
The AMP signal detection algorithm was used for solving the Least Absolute contraction and Selection Operator (LASSO) problem, and in addition, it can be used for solving the sparse signal recovery and compressed sensing problems. When the terminal device detects the transmission signal of the terminal device by using the AMP signal detection algorithm, the terminal device cannot accurately detect the transmission information because the moment matching cannot be accurately calculated.
Fig. 1a is a schematic structural diagram of a signal detection device provided by the present invention. In fig. 1a, the signal detection device 10 comprises: a Controller Unit (CU) 101, an iteration Unit 102, and a register Unit 103.
A controller unit 101 for controlling a clock and an Input/Output (I/O);
an iteration unit 102, configured to determine a target symbol parameter corresponding to the received signal during each iteration update, a corresponding probability in a modulation symbol constellation point set, and an estimated value corresponding to the transmitted signal;
register unit 103 is used to store I/O and auxiliary data, which may include, but is not limited to, the above target symbol parameters, probabilities, and estimates.
The iteration unit 102 may include: constellation processing element 1021 and parallel interference cancellation element 1022. The number of constellation processing elements 1021 is p and the number of parallel interference cancellation elements 1022 is q. Illustratively, 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, and the value of q is 4, which are the first parallel interference cancellation element, the second parallel interference cancellation element, the third parallel interference cancellation element and the fourth parallel interference cancellation element, respectively.
The register unit 103 may include: the Read Only Memory (ROM) includes a number s of register units 103, where s has a value of 4, and the number s is a first register unit, a second register unit, a third register unit, and a fourth register unit, where the first register unit is used to store a matched filter input, the second register unit is used to store a channel matrix, the third register unit is used to store an output result, and the fourth register unit is used to store auxiliary data.
The parallel interference cancellation element 1022 may include: the device comprises a calculator and a parallel interference eliminator, wherein the calculator is used for determining the probability corresponding to a received signal, and the parallel interference eliminator is used for determining the estimation value corresponding to a transmitted signal. Optionally, the calculator may include: a value change selector and a segment shift selector.
In some embodiments, as shown in fig. 1b, it is a schematic structural diagram of a constellation processing element provided in the present invention. In fig. 1b, the constellation processing element 1021 includes a Nearest Neighbor Approximation (NNA) selector (abbreviated as selector) for determining a target symbol parameter corresponding to a received signal, an adder for addition, a multiplier for multiplication, and a selection adder for performing addition after selecting data; the adder is connected with the NNA selector and the multiplier, the NNA selector and the multiplier are connected with the first flow register, the first flow register is connected with the selective adder, and the selective adder is connected with the second flow register. Alternatively, the NNA selectors can include multiplexers (MUXers) Δ and MUX Ω:
in some embodiments, as shown in fig. 1c, it is a schematic structural diagram of the parallel interference canceller provided in the present invention. In fig. 1c, the parallel interference canceller may include an averaging selector for shift plus branch selection of data and a matrix vector multiplier.
The signal detection device according to the embodiment of the present invention may detect a received signal of a terminal device using an NNA-AMP algorithm and a Hardware-Friendly (HF-AMP) signal detection algorithm.
The terminal device related to the embodiment of the present invention may include but is not limited to: mobile terminal, wearable equipment, computer, etc. The terminal equipment can be provided with a narrow-band large-scale multiple-input multiple-output M-MIMO device.
Wherein the M-MIMO device may comprise N t A transmitting antenna and N r A receiving antenna, N t ≥2,N r ≥2,N t <N r
In some embodiments, the method for modulating the received signal of the terminal device includes Q symbol Quadrature Amplitude Modulation (Q-QAM) methods in which a Modulation symbol constellation point set (abbreviated as a constellation point set) is Ω.
In the Q-QAM mode, the M-MIMO device has a complex signal transmission model of
Figure BDA0003682542880000061
Wherein,
Figure BDA0003682542880000062
a transmission matrix representing a correspondence of a wireless communication channel of the terminal device,
Figure BDA0003682542880000063
representing the received signal vector for the receive antenna,
Figure BDA0003682542880000064
representing the transmit signal vector corresponding to the transmit antenna,
Figure BDA0003682542880000067
representing a noise vector.
Exemplary, suppose
Figure BDA0003682542880000068
The rayleigh channels are distributed independently and,
Figure BDA0003682542880000066
the corresponding average value is 0 and,
Figure BDA0003682542880000065
corresponding to a noise variance of 1/N r At this time, the process of the present invention,
Figure BDA0003682542880000069
represents an Additive White Gaussian Noise (AWGN) vector,
Figure BDA00036825428800000610
the corresponding average value is 0 and,
Figure BDA00036825428800000611
corresponding to a noise variance of
Figure BDA00036825428800000612
Representing an identity matrix.
Optionally, the value of Q in the Q symbols may be one of 16, 32, 64, and 256, which is not specifically limited herein.
In some embodiments, the Channel State Information (CSI) in the terminal device includes a Channel matrix H, and the terminal device may use the complex signal transmission model described above, assuming that the CSI is known, i.e., H is known
Figure BDA00036825428800000613
Conversion to an equivalent real number model: y is Hx + n.
Wherein H representsA transmission matrix corresponding to a wireless communication channel of a terminal device, the transmission matrix having a dimension of 2N r ×2N t ,H∈R 2 Nr×2 Nt H corresponds to the corresponding algorithm related to the embodiment of the invention; y ═ y 1 ,y 2 ,…,y 2Nr ] T Denotes the received signal vector, y ∈ R 2Nr×1 ;[.] T Representing a transpose operation; x ═ x 1 ,x 2 ,…,x 2Nt ] T Denotes a transmission signal vector, x ∈ Ω 2 Nt×1 And omega represents a real number set corresponding to a real part/imaginary part in a Q-QAM constellation, and the size of the real number set is
Figure BDA0003682542880000071
n=[n 1 ,n 2 ,…,n 2Nr ] T Representing an AWGN vector, n corresponds to a mean of 0 and n corresponds to a noise variance of σ n 2
The execution main body according to the embodiment of the present invention may be a signal detection device, or may be a terminal device. The following further describes an embodiment of the present invention by taking a terminal device as an example.
As shown in fig. 2, which is a schematic flow chart of the signal detection method provided by the present invention, the method may include:
201. and determining a target symbol parameter corresponding to a received signal in the process of detecting a transmission signal of the terminal equipment.
Optionally, the target symbol parameter may include: modulation symbol constellation point set
Figure BDA0003682542880000072
Or, the nearest neighbor symbol ω, or
Figure BDA0003682542880000073
The corresponding coding flag F.
The terminal device may be included with the selector from the auxiliary data of the register unit in the course of detecting the received signal y of the terminal device
Figure BDA0003682542880000074
Determining omega; can also be based on
Figure BDA0003682542880000075
Corresponding position index m, determining the
Figure BDA0003682542880000076
The corresponding encoding flag is not specifically limited herein.
In some embodiments, the terminal device may index m according to a first preset number of positions
Figure BDA0003682542880000077
Determining nearest neighbor symbols omega corresponding to the m, wherein the number of omega is the same as that of the m; or according to the first preset number of m pairs
Figure BDA0003682542880000078
The second preset number of intervals are obtained by dividing, and the second preset number of intervals are marked with corresponding gray codes respectively to obtain a second preset number of coding marks F, which is not specifically limited herein.
The first preset quantity and the second preset quantity may be the same or different, and may be set before the terminal device leaves the factory, or may be customized by the user according to actual needs, and are not specifically limited here.
202. And determining the corresponding probability of the received signal in the modulation symbol constellation point set according to the target symbol parameter.
In some embodiments, the terminal device may determine, according to the target symbol parameter, a relationship parameter corresponding to the received signal, and then determine, according to the relationship parameter, a probability that the received signal corresponds to the modulation symbol constellation point set.
In some embodiments, the terminal device may determine the first probability corresponding to the received signal according to ω, and may also determine the second probability corresponding to the received signal according to F, which is not limited herein.
That is to say, the terminal device may determine, according to the first relation parameter corresponding to ω, a first probability corresponding to the received signal in the modulation symbol constellation point set, or may determine, according to the second relation parameter corresponding to F, a second probability corresponding to the received signal in the modulation symbol constellation point set, which is not specifically limited herein.
Optionally, before step 202, the method may further include: the terminal equipment respectively obtains a transmitting signal vector x, a receiving signal vector y, a channel matrix H and a noise variance sigma by utilizing a controller unit according to the acquired transmitting signal, receiving signal, channel state information CSI and noise information of the terminal equipment n 2 . Then, the terminal device calculates the values of x, y, H, and σ n 2 And obtaining the matched filtered received signal b corresponding to the Gram channel matrixes G and H. Wherein G ═ H T H,b=H T y。
Finally, the terminal equipment can determine the probability corresponding to the received signal by utilizing G and b.
203. Based on the probability, an estimate corresponding to the transmitted signal is determined.
In some embodiments, the terminal device may determine a detection error corresponding to the transmitted signal based on the probability, and then determine an estimated value corresponding to the transmitted signal based on the detection error.
In some embodiments, the terminal device may determine a mean value corresponding to the received signal based on the probability, and then determine a detection error corresponding to the received signal based on the mean value.
Optionally, detecting errors
Figure BDA0003682542880000081
May be obtained by the terminal device using an averaging selector in the parallel interference canceller. The terminal equipment utilizes the first adder to output the addition tree and the filtered received signal b i And combining to obtain the detection error.
Optionally, estimating the value
Figure BDA0003682542880000082
It may be that the terminal device is obtained by means of a matrix vector multiplier in the parallel interference canceller. In the matrix vector multiplier, the terminal device may multiply g i =[g i,1 ,g i,2 ,…,g i,2Nt ] T Are respectively connected with
Figure BDA0003682542880000091
Inner products are performed, each group being performed by a multiplier and a five-stage addition tree, to achieve G and
Figure BDA0003682542880000092
the multiplication of (2). Wherein, g i Representing the ith row element in G.
In the embodiment of the invention, the method is used for solving the problem that in the prior art, the terminal equipment detects the transmission signal of the terminal equipment by using an M-MIMO detection algorithm, and the whole signal detection process is complex, so that the detection hardware cost corresponding to the accurate detection of the signal is high.
As shown in fig. 3a, which is a schematic flow chart of the signal detection method provided by the present invention, the method may include:
301. in the process of detecting the transmission signal of the terminal device, in the modulation symbol constellation point set, the nearest neighbor symbol corresponding to the received signal is determined.
In the process of detecting the transmission signal of the terminal device, the terminal device may utilize the selector to perform constellation point set of modulation symbols according to the position indexes m of the first preset number
Figure BDA0003682542880000094
Then, the nearest neighbor symbol ω corresponding to m is determined.
Illustratively, the first predetermined number is 2. The terminal equipment can index and divide according to 2 positionsIs respectively the first position index m 1 And a second position index m 2 In a
Figure BDA0003682542880000093
To determine the m 1 Corresponding first nearest neighbor symbol ω m1 And determining the m 2 Corresponding second nearest neighbor symbol ω m2
Wherein m is 1 And m 2 Is randomly drawn by the terminal device.
302. And determining a first relation parameter according to the nearest neighbor symbol, and determining a corresponding first probability of the received signal in the modulation symbol constellation point set according to the first relation parameter.
In some embodiments, a large number of processing nodes exist in a Signal Flow Graph (SFG) corresponding to the terminal device. The terminal device can delete part of processing nodes with low performance dependency from the SFG to achieve the purpose of compressing the processing nodes, so as to improve the processing efficiency of other processing nodes.
At this time, the terminal device may be based on a dynamic formula
Figure BDA0003682542880000108
Obtaining the noise variance tau corresponding to the terminal equipment (l) . However, because the beta factor of the transmission model corresponding to the M-MIMO device in the terminal equipment is small, therefore,
Figure BDA0003682542880000109
are negligible. The terminal device may then formulate the dynamic equation
Figure BDA00036825428800001010
Can be simplified to a static formula tau (l) =σ n Thereby obtaining more accurate noise variance tau (l)
Optionally, the determining, by the terminal device, the first relationship parameter according to the nearest neighbor symbol, and determining, according to the first relationship parameter, a corresponding first probability of the received signal in the modulation symbol constellation point set may include: and the terminal equipment determines a first relation parameter according to a first parameter formula and determines a corresponding first probability of the received signal in the modulation symbol constellation point set according to a first probability formula.
Wherein the first parameter formula is
Figure BDA0003682542880000101
Figure BDA0003682542880000102
l represents the number of iterations,
Figure BDA0003682542880000103
representing a first relation parameter, s ω =ω m2m1 Representing the difference between the second nearest neighbor symbol and the first nearest neighbor symbol, a ω =ω m2m1 Representing the sum of the second nearest neighbor symbol and the first nearest neighbor symbol,
Figure BDA0003682542880000104
expressing a normalization parameter corresponding to the terminal equipment;
the first probability formula is
Figure BDA0003682542880000105
m represents a position index of the position,
Figure BDA0003682542880000106
representing a first probability;
Figure BDA0003682542880000107
representing the corresponding probability of the received signal in the set of modulation symbol constellation points in case the position index is the first nearest neighbor symbol.
In some embodiments, | · | in the first parameter equation can be obtained by the terminal device using the value change selector in the calculator,
Figure BDA0003682542880000111
can be obtained by the terminal equipment by utilizing a segment shift selector in a calculator。
In some embodiments, in order to simplify the computation complexity caused by the nonlinear computation portions such as division, exponent, and the like included in the first parameter formula and the first probability formula, the terminal device may perform piece-wise Linear Approximation (PLA) on the nonlinear computation portion, so that the terminal device appropriately approximates the nonlinear portion to the Linear portion in a limited numerical value interval with some data, so as to reduce the computation performance loss of the calculator and improve the accuracy of the computation result.
In the first parametric formula, the nonlinear function is
Figure BDA0003682542880000112
The terminal equipment can firstly get tau (l) Cutting at [. eta. ] a,1 ,η b,1 ]Within range of η a,1 Representing a first noise threshold, η b,1 Representing a second noise threshold; the terminal device then utilizes a signal having N seg,1 Piecewise linear interpolation function of a segment
Figure BDA0003682542880000113
To approximate the nonlinear function as
Figure BDA0003682542880000114
N seg,1 A first number is indicated.
In the first probability formula, the nonlinear function is
Figure BDA0003682542880000115
Wherein,
Figure BDA0003682542880000116
Figure BDA0003682542880000117
when the temperature is higher than the set temperature
Figure BDA0003682542880000118
When the value of (a) is small enough,
Figure BDA0003682542880000119
may be approximately equal to 0. The terminal equipment can firstly
Figure BDA00036825428800001110
Cutting at [. eta. ] a,2 ,η b,2 ]Within range of η a,2 Representing a third noise threshold, η b,2 Representing a fourth noise threshold, η b,2 Is 0; the terminal device then utilizes a signal having N seg,2 Piecewise linear function approximation of segments
Figure BDA00036825428800001111
N seg,2 A second number is indicated. That is, the terminal device utilizes a linear interpolation function
Figure BDA00036825428800001112
To replace non-linear functions
Figure BDA00036825428800001113
Exemplarily, as shown in fig. 3b, it is a schematic diagram of performance simulation corresponding to the signal detection method provided by the present invention. In FIG. 3b, the curve connecting the blocks is N before the processing node is deleted t =8、N t 16 and N t 32 corresponding Bit Error Rate (BER) variation curves respectively; after the triangle-connected curve is deleted for the processing node, N t =8、N t 16 and N t The BER curves correspond to 32, respectively. Wherein E is s Representing the average energy, N, of the corresponding symbols of the received signal 0 Representing the corresponding channel noise power of the terminal device.
By comparison of two BER curves, at N t 8 and N t When the value is 16, the terminal device replaces the nonlinear function with the linear interpolation function to obtain a result with a smaller BER.
Exemplarily, as shown in fig. 3c, it is a schematic diagram of performance simulation corresponding to the signal detection method provided by the present invention. FIG. 3c is a variation
Figure BDA0003682542880000121
Respectively corresponding BER curves. In FIG. 3c, at η a,1 =1/8,η b,1 15/8 and N seg,1 When the BER is 1, the terminal device replaces the nonlinear function with the linear interpolation function, and the obtained result has a smaller BER.
As shown in fig. 3d, it is a schematic diagram of performance simulation corresponding to the signal detection method provided by the present invention. In FIG. 3d, at η a,2 =-4,η b,2 0 and N seg,2 When the BER is 1, the terminal device replaces the nonlinear function with the linear interpolation function, and the obtained result has a smaller BER.
In some embodiments, the end device may store all of the above mentioned values that may be involved in a Look-Up Table (LUT) of the register unit. Alternatively, the terminal device may store all of the above mentioned values that may be involved in the PLA, which 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. Compared with a traditional Coordinate Rotation Digital Computer (CORDIC) algorithm, the method for obtaining corresponding data by the terminal device based on the PLA can reduce processing time delay of the whole calculation process to a certain extent, that is, can reduce processing time of a multiplier and an adder to a certain extent.
303. And determining an estimation value corresponding to the transmission signal according to an estimation formula.
Wherein the estimation formula is
Figure BDA0003682542880000122
Represents an estimated value, m 1 Denotes a first position index, ω m1 Denotes a first nearest neighbor symbol, m, corresponding to a first position index 2 Representing the second position index, ω m2 Indicating the second nearest neighbor symbol to which the second position index corresponds,
Figure BDA0003682542880000123
is shown in the firstIn the case of nearest neighbor symbols, a first target probability of correspondence of the received signal in the set of modulation symbol constellation points,
Figure BDA0003682542880000131
representing a corresponding second target probability of the received signal in the set of modulation symbol constellation points in case of a second nearest neighbor symbol.
Optionally, after step 303, the method may further include: the terminal device transmits an estimated value corresponding to the signal, and determines a detection error between the transmitted signal and the output signal.
Optionally, the determining, by the terminal device, a detection error between the transmission signal and the output signal according to the estimated value corresponding to the transmission signal may include: and the terminal equipment determines the detection error between the transmission signal and the output signal according to an error formula.
Wherein the error formula is
Figure BDA0003682542880000132
l represents the number of iterations;
Figure BDA0003682542880000133
indicating a detection error, b i I-th received signal, g, of matched filtered received signals corresponding to a channel matrix representing a terminal device i,j The (i, j) -th element in the gram channel matrix G representing the terminal device, G ═ H T H, H represents a transmission matrix corresponding to a wireless communication channel of the terminal equipment,
Figure BDA0003682542880000134
indicating the corresponding estimate for the jth transmitted signal.
It will be appreciated that since the estimate obtained by the electronic device is relatively accurate, the detection error between the transmitted signal and the output signal determined by the electronic device based on the estimate is also relatively small.
In the embodiment of the invention, the terminal equipment can detect the transmission signal of the terminal equipment by utilizing the NNA-AMP algorithm. The method is used for solving the problem that the terminal equipment detects the transmission signal of the terminal equipment by utilizing an M-MIMO detection algorithm in the prior art, and the detection hardware cost corresponding to the accurate detection of the signal is higher due to the fact that the whole signal detection process is complex.
As shown in fig. 4a, which is a schematic flow chart of the signal detection method provided by the present invention, the method may include:
401. and in the process of detecting the transmission signal of the terminal equipment, determining a corresponding coding mark of the received signal in the modulation symbol constellation point set according to the position index corresponding to the modulation symbol constellation point set.
The terminal device may utilize the selector to index m pairs according to a first preset number of positions in the process of detecting the received signal of the terminal device
Figure BDA0003682542880000141
And dividing to obtain intervals of a second preset number, and marking the intervals of the second preset number by using corresponding gray codes respectively to obtain coding marks F of the second preset number.
Illustratively, the first predetermined number is 2 and the second predetermined number is 6. The terminal device can be according to m 1 And m 2 Will be provided with
Figure BDA0003682542880000142
Is divided into 6 intervals which are respectively (- ∞ -2)]、(-2,-1]、(-1,0]、(0,1]、(1,2]And (2, + ∞); then, the terminal device marks the 6 intervals with corresponding gray codes, and obtains 6 code marks F which are respectively F 1 、F 2 、F 3 、F 4 、F 5 And F 6
Alternatively, { F 4 ,F 5 May be a result of MUX- Δ that the selector includes, { F } F 1 ,F 2 ,F 3 May be derived from a MUX-omega selector comprised by the selector.
402. And determining a second relation parameter according to the coding mark, and determining a corresponding second probability of the transmission signal in the modulation symbol constellation point set according to the second relation parameter.
Optionally, the terminal device may calculate a based on the 6 intervals ω And s ω
Wherein, a ω There may be 3 possible values, respectively-4, 0 and 4, in different intervals, and the terminal device may determine a ω Corresponding code flag { F 4 ,F 5 Is and { F } 4 ,F 5 Corresponding gray codes are 01, 11 and 10 respectively; s ω There will be 2 possible values in different intervals, respectively-2 and 2, and the terminal device can determine s ω Corresponding code flag { F 6 Is and { F } 6 The corresponding gray codes are 0 and 1, respectively. Therefore, the terminal device may reduce the first parameter formula in step 302 to the second parameter formula.
In some embodiments, since the terminal has replaced the nonlinear function with a linear interpolation function, the terminal device may reduce the first parameter formula to a second parameter formula and may reduce the first probability formula to a second probability formula.
Optionally, the determining, by the terminal device, the second relation parameter according to the coding flag, and determining, according to the second relation parameter, a second probability corresponding to the transmission signal in the modulation symbol constellation point set may include: and the terminal equipment determines a second relation parameter according to a second parameter formula and determines a corresponding second probability of the received signal in the modulation symbol constellation point set according to a second probability formula.
Wherein the second parameter formula is
Figure BDA0003682542880000151
l represents the number of iterations,
Figure BDA0003682542880000152
representing a second relational parameterThe number of the first and second groups is counted,
Figure BDA0003682542880000153
representing a corresponding normalization parameter, τ, of the terminal device (l) =σ n 2 Representing the noise variance, F, for the terminal device 4 Denotes a first encoding flag, F5 denotes a second encoding flag;
the second probability formula is
Figure BDA0003682542880000154
Representing a corresponding first target probability of the received signal in the set of modulation symbol constellation points in case of a first nearest neighbor symbol;
Figure BDA0003682542880000155
representing a corresponding second target probability of the received signal in the set of modulation symbol constellation points in case of a second nearest neighbor symbol.
In the alternative,
Figure BDA0003682542880000156
and
Figure BDA0003682542880000157
the terminal device may use the absolute value + calculator in the calculator.
Illustratively, the terminal device will interpolate the function linearly
Figure BDA0003682542880000158
The quantization slope in (1) is taken to be 0.5, and the quantization intercept is taken to be-0.125.
At this time, the process of the present invention,
Figure BDA0003682542880000159
403. and determining an estimation value corresponding to the transmission signal according to an estimation formula.
It should be noted that the process of determining, by the terminal device, the estimated value corresponding to the transmitted signal according to the estimation formula in step 403 is similar to the process of determining, by the terminal device, the estimated value corresponding to the transmitted signal according to the estimation formula in step 303 shown in fig. 3, and details are not described here.
Due to the first relation parameter in step 302
Figure BDA0003682542880000161
And s ω Irrelevant, therefore, the terminal equipment does not need to encode the flag { F ] in the process of simplifying the first parameter formula 6 }. Then, when determining an estimated value corresponding to a transmission signal by using the parallel interference canceller, the terminal device may simplify the multiplication operation of the integer constellation to a Shift And Add (SAA) operation by sub-expression sharing.
For example, an electronic device may share data via sub-expressions
Figure BDA0003682542880000162
Simplified to a mean table.
The mean values are listed below:
Figure BDA0003682542880000163
optionally, after step 303, the method may further include: and the terminal equipment determines the mean value corresponding to the received signal based on the probability, and determines the detection error between the transmitted signal and the received signal according to the mean value.
Optionally, the determining, by the terminal device, a mean value corresponding to the received signal based on the probability, and determining a detection error between the transmitted signal and the received signal according to the mean value may include: and the terminal equipment calculates the mean value corresponding to the received signal according to the mean value table, and determines the detection error between the transmitted signal and the received signal according to the mean value.
That is, the terminal device utilizes the parallel interference canceller based on different { F } 1 ,F 2 ,F 3 And fourthly, the obtained mean values are also different, and then the terminal equipment can accurately determine the detection error corresponding to the received signal according to the mean values.
It will be appreciated that since the estimate obtained by the electronic device is relatively accurate, the detection error between the transmitted signal and the output signal determined by the electronic device based on the estimate is also relatively small.
In some embodiments, when Nr is 8 and Nt is 128 in the M-MIMO apparatus, the modulation scheme corresponding to the received signal of the terminal device is 16-QAM. Through simulation verification, in the process that the terminal equipment utilizes the AMP algorithm, the NAA-AMP algorithm and the HF-AMP algorithm to detect the received signals, the performance parameters of the terminal equipment are basically consistent under different iteration times of each algorithm, and the terminal equipment is converged when the iteration times are L-4, so that the accuracy of transmission information detection is improved. Wherein the AMP algorithm may be integrated on the AMP detector, the HF-AMP algorithm may be integrated on the HF-AMP detector, and the HF-AMP algorithm may be integrated on the HF-AMP detector.
Secondly, the terminal device needs to quantify all the variables involved: fig. 4b is a schematic diagram of the simulation result provided by the present invention. In fig. 4b, the HF-AMP with 4-bit fractional and 5-bit fractional part bit widths suffers from severe performance degradation. An HF-AMP with a 6-bit fractional part bit width can almost perfectly restore the performance of a floating point HF-AMP. Thus, the quantization scheme for HF-AMP is taken to be 1-6-6.
And finally, further completing the hardware realization and verification based on a Field Programmable Gate Array (FPGA). The quantized HF-AMP algorithm is implemented using a Xilinx Virtex-7 Ultrascale vu440-flga2892-2-e FPGA.
Finally, an Application Specific Integrated Circuit (ASIC) is implemented, the HF-AMP detector detects the received signal using the SMIC 65nm LL 1P9MCMOS technique, the HF-AMP detector is Integrated in Design compilation (Design Compiler) software of Synopsys, and as a result, the layout and wiring are performed using Design flow guide (IC Compiler) software of Synopsys. The annotation flip rate of the gate-level netlist is converted to a Switching Activity Interchange Format (SAIF) of an environment (Prime-Time) PX to measure Time-based pure chip power consumption.
Further, the hardware corresponding to the final HF-AMP detector realizes the high throughput rate of 10.56Gb/s under a clock of 330MHz, and basically reaches the highest level in the industry, and meanwhile, the overall power consumption is guaranteed to be 103.76 mW. Under the condition of high throughput area ratio of 5.03, unit bit energy consumption is guaranteed to be 9.83pJ/b, a high-efficiency hardware architecture is realized, and the method has a future prospect of green and energy conservation.
In the embodiment of the present invention, the terminal device may detect the transmission signal of the terminal device by using an HF-AMP signal detection algorithm. The method is used for solving the problem that in the prior art, the terminal equipment detects the transmission signal of the terminal equipment by using an M-MIMO detection algorithm, and the detection hardware cost corresponding to the accurate detection of the signal is higher due to the fact that the whole signal detection process is complex.
The signal detection device provided by the present invention is described below, and the signal detection device described below and the signal detection method described above may be referred to in correspondence with each other.
As shown in fig. 5, which is a schematic structural diagram of a signal detection apparatus provided by the present invention, the signal detection apparatus may include:
a selecting module 501, configured to determine a target symbol parameter corresponding to a received signal in a process of detecting a transmission signal of a terminal device;
a calculating module 502, configured to determine, according to the target symbol parameter, a corresponding probability of the received signal in a modulation symbol constellation point set;
and a parallel interference cancellation module 503, configured to determine an estimated value corresponding to the transmission signal based on the probability.
Optionally, the selecting module 501 is specifically configured to determine, in the modulation symbol constellation point set, a nearest neighbor symbol corresponding to the received signal; or, determining the corresponding coding mark of the received signal in the modulation symbol constellation point set number according to the position index corresponding to the modulation symbol constellation point set.
Optionally, the calculating module 502 is specifically configured to determine a first relation parameter according to the nearest neighbor symbol, and determine a corresponding first probability of the received signal in the modulation symbol constellation point set according to the first relation parameter.
Optionally, the calculating module 502 is specifically configured to determine a first relation parameter according to a first parameter formula, and determine a corresponding first probability of the received signal in the modulation symbol constellation point set according to a first probability formula; the first parameter is expressed as
Figure BDA0003682542880000191
l represents the number of iterations,
Figure BDA0003682542880000192
represents the first relation parameter, m 1 Denotes a first position index, ω m1 Indicating the first nearest neighbor symbol, m, corresponding to the first position index 2 Representing the second position index, ω m2 Indicating a second nearest neighbor symbol corresponding to the second position index; s ω =ω m2m1 Representing the difference between the second nearest neighbor symbol and the first nearest neighbor symbol, a ω =ω m2m1 Denotes the sum of the second nearest neighbor symbol and the first nearest neighbor symbol, τ (l) =σ n 2 Representing the noise variance corresponding to the channel matrix in the terminal equipment,
Figure BDA0003682542880000193
indicating the corresponding normalization parameter of the terminal device,
Figure BDA0003682542880000194
representing the set of modulation symbol constellation points; the first probability formula is
Figure BDA0003682542880000195
m represents a position index of the position,
Figure BDA0003682542880000196
representing the first probability;
Figure BDA0003682542880000197
indicating the corresponding probability of the received signal in the set of modulation symbol constellation points if the position index is the first nearest neighbor symbol.
Optionally, the calculating module 502 is specifically configured to determine a second relation parameter according to the coding flag, and determine a second probability corresponding to the transmission signal according to the second relation parameter.
Optionally, the calculating module 502 is specifically configured to determine a second relation parameter according to a second parameter formula, and determine a second probability corresponding to the received signal in the modulation symbol constellation point set according to a second probability formula; the second parameter is expressed as
Figure BDA0003682542880000201
l represents the number of iterations,
Figure BDA0003682542880000202
the second relation parameter is represented by a second relation parameter,
Figure BDA0003682542880000203
indicating the corresponding normalization parameters of the terminal device,
Figure BDA0003682542880000204
represents the set of modulation symbol constellation points, τ (l) =σ n 2 Representing the noise variance, F, corresponding to the channel matrix in the terminal equipment 4 Denotes a first encoding flag, F5 denotes a second encoding flag; the second probability formula is
Figure BDA0003682542880000205
m 1 Denotes a first position index, ω m1 Indicating the first nearest neighbor symbol, m, corresponding to the first position index 2 Representing the second position index, ω m2 Indicating the second nearest neighbor symbol to which the second position index corresponds,
Figure BDA0003682542880000206
representing a corresponding first target probability of the received signal in the set of modulation symbol constellation points in case of the first nearest neighbor symbol;
Figure BDA0003682542880000207
representing a corresponding second target probability of the received signal in the set of modulation symbol constellation points in the case of the second nearest neighbor symbol.
Optionally, the parallel interference cancellation module 503 is specifically configured to determine an estimation value corresponding to the transmission signal according to an estimation formula; the estimation formula is
Figure BDA0003682542880000208
Figure BDA0003682542880000209
Represents the estimated value, m 1 Denotes a first position index, ω m1 Indicating the first nearest neighbor symbol, m, corresponding to the first position index 2 Representing the second position index, ω m2 Indicating the second nearest neighbor symbol to which the second position index corresponds,
Figure BDA00036825428800002010
representing a corresponding first target probability of the received signal in the set of modulation symbol constellation points in case of the first nearest neighbor symbol,
Figure BDA0003682542880000211
representing a corresponding second target probability of the received signal in the set of modulation symbol constellation points in case of the second nearest neighbor symbol.
Fig. 6 illustrates a physical structure diagram of an electronic device, which may include, as shown in fig. 6: a processor (processor)610, a communication Interface (Communications Interface)620, a memory (memory)630 and a communication bus 640, wherein the processor 610, the communication Interface 620 and the memory 630 communicate with each other via the communication bus 640. The processor 610 may include a selector 6101, a calculator 6102, and a parallel interference canceller 6103, and the processor 610 may invoke logic instructions in the memory 630 to perform a signal detection method comprising: determining a target symbol parameter corresponding to a received signal in the process of detecting a transmission signal of terminal equipment; determining the probability of the received signal in a modulation symbol constellation point set according to the target symbol parameter; based on the probability, an estimated value corresponding to the transmission signal is determined.
In addition, the logic instructions in the memory 630 may be implemented in software functional units and stored in a computer readable storage medium when the logic instructions are sold or used as independent products. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
In another aspect, the present invention also provides a computer program product, the computer program product comprising a computer program, the computer program being storable on a non-transitory computer-readable storage medium, the computer program, when executed by a processor, being capable of executing the signal detection method provided by the above methods, the method comprising: determining a target symbol parameter corresponding to a received signal in the process of detecting a transmission signal of terminal equipment; determining the probability of the received signal in the modulation symbol constellation point set according to the target symbol parameter; based on the probability, an estimated value corresponding to the transmission signal is determined.
In yet another aspect, the present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored, the computer program being implemented by a processor to perform the signal detection method provided by the above methods, the method comprising: determining a target symbol parameter corresponding to a received signal in the process of detecting a transmission signal of terminal equipment; determining the probability of the received signal in a modulation symbol constellation point set according to the target symbol parameter; based on the probability, an estimated value corresponding to the transmission signal is determined.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.

Claims (10)

1. A method of signal detection, comprising:
determining a target symbol parameter corresponding to a received signal in the process of detecting a transmission signal of terminal equipment;
determining the probability of the received signal in a modulation symbol constellation point set according to the target symbol parameter;
and determining an estimated value corresponding to the transmission signal based on the probability.
2. The signal detection method of claim 1, wherein the determining the target symbol parameter corresponding to the received signal comprises:
determining a nearest neighbor symbol corresponding to a received signal in the modulation symbol constellation point set;
or,
and determining a corresponding coding mark of the received signal in the modulation symbol constellation point set number according to the position index corresponding to the modulation symbol constellation point set.
3. The method according to claim 2, wherein in the case that the nearest neighbor symbol corresponding to the received signal is determined in the modulation symbol constellation point set, the determining, according to the target symbol parameter, the probability that the received signal corresponds to the modulation symbol constellation point set comprises:
and determining a first relation parameter according to the nearest neighbor symbol, and determining a corresponding first probability of the received signal in a modulation symbol constellation point set according to the first relation parameter.
4. The method according to claim 3, wherein the determining a first relation parameter according to the nearest neighbor symbol and determining a corresponding first probability of the received signal in a modulation symbol constellation point set according to the first relation parameter comprises:
determining a first relation parameter according to a first parameter formula, and determining a corresponding first probability of the received signal in a modulation symbol constellation point set according to a first probability formula;
the first parameter formula is
Figure FDA0003682542870000011
Figure FDA0003682542870000012
l represents the number of iterations,
Figure FDA0003682542870000013
represents the first relation parameter, m 1 Denotes a first position index, ω m1 Representing a first nearest neighbor symbol, m, corresponding to the first position index 2 Denotes a second position index, ω m2 Representing a second nearest neighbor symbol corresponding to the second position index; s is ω =ω m2m1 Representing the difference between the second nearest neighbor symbol and the first nearest neighbor symbol, a ω =ω m2m1 Representing the sum of the second nearest neighbor symbol and the first nearest neighbor symbol, τ (l) =σ n 2 Representing the noise variance corresponding to the channel matrix in the terminal equipment,
Figure FDA0003682542870000021
representing a normalization parameter corresponding to the terminal device,
Figure FDA0003682542870000022
representing the set of modulation symbol constellation points;
the first probability formula is
Figure FDA0003682542870000023
m represents a position index of the position,
Figure FDA0003682542870000024
representing the first probability;
Figure FDA0003682542870000025
representing a probability that the received signal corresponds in the set of modulation symbol constellation points if the position index is the first nearest neighbor symbol.
5. The method according to claim 2, wherein in a case that the code flag corresponding to the received signal in the modulation symbol constellation point set number is determined according to the position index corresponding to the modulation symbol constellation point set, the determining, according to the target symbol parameter, the probability that the received signal corresponds in the modulation symbol constellation point set includes:
and determining a second relation parameter according to the coding mark, and determining a corresponding second probability of the received signal in the modulation symbol constellation point set according to the second relation parameter.
6. The method according to claim 5, wherein the determining a second relation parameter according to the coding flag, and determining a corresponding second probability of the received signal in the modulation symbol constellation point set according to the second relation parameter comprises:
determining a second relation parameter according to a second parameter formula, and determining a corresponding second probability of the received signal in a modulation symbol constellation point set according to a second probability formula;
the second parameter formula is
Figure FDA0003682542870000031
l represents the number of iterations,
Figure FDA0003682542870000032
represents the second relation parameter in the second set of relations,
Figure FDA0003682542870000033
representing a normalization parameter corresponding to the terminal device,
Figure FDA0003682542870000034
representing said set of modulation symbol constellation points, τ (l) =σ n 2 Representing the noise variance, F, corresponding to the channel matrix in said terminal equipment 4 Denotes a first encoding flag, F5 denotes a second encoding flag;
the second probability formula is
Figure FDA0003682542870000035
m 1 Denotes a first position index, ω m1 Representing a first nearest neighbor symbol, m, corresponding to the first position index 2 Denotes a second position index, ω m2 Representing a second nearest neighbor symbol corresponding to the second position index;
Figure FDA0003682542870000036
representing a corresponding first target probability of the received signal in the set of modulation symbol constellation points with the first nearest neighbor symbol;
Figure FDA0003682542870000037
represents a corresponding second target probability of the received signal in the set of modulation symbol constellation points in the case of the second nearest neighbor symbol.
7. The signal detection method of claim 4 or 6, wherein the determining the corresponding estimated value of the transmission signal based on the probability comprises:
determining an estimation value corresponding to a transmission signal according to an estimation formula;
the estimation formula is
Figure FDA0003682542870000038
Figure FDA0003682542870000039
Represents said estimated value, m 1 Denotes a first position index, ω m1 Representing a first nearest neighbor symbol, m, corresponding to the first position index 2 Denotes a second position index, ω m2 Representing a second nearest neighbor symbol to which the second position index corresponds,
Figure FDA00036825428700000310
representing a corresponding first target probability of the received signal in the set of modulation symbol constellation points in case of the first nearest neighbor symbol,
Figure FDA0003682542870000041
represents a corresponding second target probability of the received signal in the set of modulation symbol constellation points in the case of the second nearest neighbor symbol.
8. A signal detection device, comprising:
the selection module is used for determining a target symbol parameter corresponding to a received signal in the process of detecting a transmission signal of the terminal equipment;
a calculating module, configured to determine, according to the target symbol parameter, a corresponding probability of the received signal in a modulation symbol constellation point set;
and the parallel interference elimination module is used for determining an estimated value corresponding to the sending signal based on the probability.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor comprises a selector, a calculator and a parallel interference canceller, and wherein the processor implements the signal detection method according to any one of claims 1 to 7 when executing the program.
10. A non-transitory computer-readable storage medium having stored thereon a computer program, wherein the computer program, when executed by a processor, implements the signal detection method according to any one of claims 1 to 7.
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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2023236610A1 (en) * 2022-06-07 2023-12-14 网络通信与安全紫金山实验室 Signal detection method and apparatus, and electronic device and storage medium

Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2010092437A1 (en) * 2009-02-12 2010-08-19 Nokia Corporation Method and apparatus for providing transmission relay using soft symbol estimation
US20110058632A1 (en) * 2009-09-04 2011-03-10 Politecnico Di Milano Method and device for soft-output detection in multiple antenna communication systems
US8166379B1 (en) * 2006-11-03 2012-04-24 Marvell International Ltd. Calculating soft information from a multi-level modulation signal
US9325427B1 (en) * 2012-10-31 2016-04-26 Ciena Corporation Maximum likelihood decoding
US9929813B1 (en) * 2017-03-06 2018-03-27 Tyco Electronics Subsea Communications Llc Optical communication system and method using a nonlinear reversible code for probablistic constellation shaping
CN109474552A (en) * 2017-09-08 2019-03-15 北京科技大学 Soft symbol estimation method, receiver and computer-readable medium
CN114070694A (en) * 2020-07-30 2022-02-18 华为技术有限公司 Method and apparatus for wireless communication
CN114301545A (en) * 2021-12-03 2022-04-08 网络通信与安全紫金山实验室 Signal detection method, signal detection device, electronic equipment and storage medium

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CA2541567C (en) * 2006-03-31 2012-07-17 University Of Waterloo Parallel soft spherical mimo receiver and decoding method
CN101383652B (en) * 2007-09-04 2012-09-26 中兴通讯股份有限公司 Signal detection method and apparatus for MIMO system
CN112398535B (en) * 2020-10-27 2021-10-29 天津大学 Method for improving transmission capacity of non-orthogonal multiple access visible light communication based on probability shaping
CN115037340B (en) * 2022-06-07 2023-11-07 网络通信与安全紫金山实验室 Signal detection method, device, electronic equipment and storage medium

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8166379B1 (en) * 2006-11-03 2012-04-24 Marvell International Ltd. Calculating soft information from a multi-level modulation signal
WO2010092437A1 (en) * 2009-02-12 2010-08-19 Nokia Corporation Method and apparatus for providing transmission relay using soft symbol estimation
US20110058632A1 (en) * 2009-09-04 2011-03-10 Politecnico Di Milano Method and device for soft-output detection in multiple antenna communication systems
US9325427B1 (en) * 2012-10-31 2016-04-26 Ciena Corporation Maximum likelihood decoding
US9929813B1 (en) * 2017-03-06 2018-03-27 Tyco Electronics Subsea Communications Llc Optical communication system and method using a nonlinear reversible code for probablistic constellation shaping
CN109474552A (en) * 2017-09-08 2019-03-15 北京科技大学 Soft symbol estimation method, receiver and computer-readable medium
CN114070694A (en) * 2020-07-30 2022-02-18 华为技术有限公司 Method and apparatus for wireless communication
CN114301545A (en) * 2021-12-03 2022-04-08 网络通信与安全紫金山实验室 Signal detection method, signal detection device, electronic equipment and storage medium

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2023236610A1 (en) * 2022-06-07 2023-12-14 网络通信与安全紫金山实验室 Signal detection method and apparatus, and electronic device and storage medium

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