CN112202479A - Low-complexity signal detection method for MIMO-orthogonal time-frequency space system - Google Patents

Low-complexity signal detection method for MIMO-orthogonal time-frequency space system Download PDF

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CN112202479A
CN112202479A CN202010837850.2A CN202010837850A CN112202479A CN 112202479 A CN112202479 A CN 112202479A CN 202010837850 A CN202010837850 A CN 202010837850A CN 112202479 A CN112202479 A CN 112202479A
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高晖
程俊强
许文俊
别志松
陆月明
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Beijing University of Posts and Telecommunications
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    • 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
    • H04B7/0617—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 for beam forming
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/0202—Channel estimation
    • H04L25/024—Channel estimation channel estimation algorithms
    • H04L25/0242—Channel estimation channel estimation algorithms using matrix methods
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/0202—Channel estimation
    • H04L25/024—Channel estimation channel estimation algorithms
    • H04L25/0242—Channel estimation channel estimation algorithms using matrix methods
    • H04L25/0244—Channel estimation channel estimation algorithms using matrix methods with inversion
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/0202—Channel estimation
    • H04L25/024—Channel estimation channel estimation algorithms
    • H04L25/025—Channel estimation channel estimation algorithms using least-mean-square [LMS] method
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
    • H04L25/03878—Line equalisers; line build-out devices

Abstract

The invention discloses a signal detection method of a MIMO-orthogonal time-frequency space system, which comprises the following steps: transmitting orthogonal time-frequency space signals at a transmitting end through an antenna array and a beam forming technology; after the transmitting signal passes through the time-varying multipath channel, a receiving signal forms a plurality of branches at a receiving end through an antenna array and a beam forming network; acquiring a delay-Doppler domain received signal of each branch; vectorizing the received signal to obtain a system input-output relation of time delay-Doppler domain vectorization; designing a low-complexity minimum mean square error equalizer based on the input-output relation of the time delay-Doppler domain vectorization system; performing soft demodulation on the output of the low-complexity minimum mean square error equalizer, and outputting corresponding log-likelihood ratio information; carrying out maximum ratio combination on the soft demodulation result of each branch, and calculating the joint log-likelihood ratio of all the branches; and judging the transmitting information according to the joint log-likelihood ratio, and outputting a judgment result.

Description

Low-complexity signal detection method for MIMO-orthogonal time-frequency space system
Technical Field
The invention relates to a mobile communication technology, in particular to a low-complexity signal detection method of a multiple-input multiple-output-orthogonal time-frequency space system.
Background
High mobility scenarios (such as high-speed rail, unmanned plane, internet of vehicles) are one of the important scenarios for future wireless communication networks (5G/B5G), in which highly dynamic channels exhibit double dispersion properties, including time dispersion due to multipath and frequency dispersion due to doppler spread. Orthogonal Frequency Division Multiplexing (OFDM) is one of the most widely used communication technologies, and is mainly used to combat Inter Symbol Interference (ISI) caused by time dispersion. However, in a high dynamic scenario, loss of orthogonality between subcarriers due to frequency dispersion may generate severe Inter-subcarrier Interference (ICI), which may significantly impair performance of the current OFDM system.
In this case, an Orthogonal Time Frequency Space (OTFS) modulation technique is developed. Specifically, an OTFS system applying an OTFS modulation technique first carries transmission information in a delay-doppler domain, and expands each delay-doppler domain information symbol to a whole time-frequency domain within a certain range at a transmitting end through Inverse Symplectic Finite Fourier Transform (ISFFT), thereby ensuring that each symbol in an OTFS frame experiences a relatively stable channel, i.e., a double-dispersion channel is converted into a channel approximately free of frequency/time dispersion in the delay-doppler domain. At the receiving end, the OTFS system converts the received information of the time-frequency domain into a delay-doppler domain through a Symplectic Finite Fourier Transform (SFFT) to perform operations such as equalization and the like, so as to combat ICI caused by a high-speed moving scene. Therefore, the OTFS, as a novel multi-carrier modulation technique, can effectively combat a highly dynamic communication channel environment, and exhibits strong robustness to high doppler spread.
As one of candidate technologies of future wireless communication networks, a Multiple-input Multiple-output (Multiple-input Multiple-output) -orthogonal time-frequency space (MIMO-OTFS) system is expected to obtain high spectral efficiency and maintain robustness to high dynamics. But such an acquisition of superior properties requires a low complexity equalization detection method to assist in designing a feasible receiver.
The existing balance detection technology of the OTFS system is mainly divided into two types: the first is a nonlinear equalization method, which has good bit error rate performance but high complexity, so the practicability is low; the second type is linear equalization, but conventional linear equalization techniques generally involve inverting the channel matrix, and the complexity of matrix inversion and matrix multiplication is O ((NM)3) Wherein, N is the number of OTFS symbols, and M is the number of subcarriers. Clearly, this complexity is unacceptable for the larger data dimensions in real-world communications, particularly for MIMO systems.
Disclosure of Invention
In view of this, the embodiment of the present invention provides a low complexity signal detection method for mimo-ofdm system.
The method may specifically include: the transmitting terminal transmits OTFS signals through a transmitting antenna array and a beam forming network; the transmitting signal passes through a time-varying multipath channel to obtain a time domain receiving signal; the receiving end forms a time domain receiving signal of a plurality of branches for the time domain receiving signal through a receiving antenna array and a beam forming network; forming time delay-Doppler domain receiving signals of a plurality of branches by the OTFS demodulation module for the time domain receiving signals of the plurality of branches; performing low-complexity Minimum Mean Square Error (MMSE) on the time delay-Doppler domain received signal, and outputting an equalization result; performing soft demodulation on the balance result of each branch, and outputting Log-Likelihood Ratio information (Log-likehood Ratio, LLR); performing combined log-likelihood Ratio calculation on the log-likelihood Ratio information of each branch based on a Maximum Ratio Combining (MRC) method; and judging the transmission information according to the combined log-likelihood ratio, and outputting a judgment result.
Wherein, the OTFS transmission signal may include: performing ISFFT and windowing operation on two-dimensional information generated in a time delay-Doppler domain to obtain corresponding time-frequency domain two-dimensional information; and carrying out OFDM modulation on the time-frequency domain two-dimensional information to generate a time domain transmitting signal.
The time-varying multipath channel may include: time-varying channel caused by relative motion of the transceiving ends; and Doppler frequency offset and inter-subcarrier interference caused by channel time-varying; multiple propagation paths caused by reflectors in the channel; as well as channel delays and intersymbol interference caused by multiple propagation paths.
Wherein, the receiving antenna array and the beam forming network may include: the time domain signal reaching the receiving end comprises incoming waves of all azimuth angles of a channel; the beam forming network only receives the incoming waves in the target direction, and suppresses the incoming waves in other directions.
Wherein, the performing OTFS demodulation on the received signal of each branch to obtain the received signal of each branch delay-doppler domain includes: OFDM demodulation is carried out on the received time domain signals of each branch, and time-frequency domain two-dimensional signals are generated; and performing windowing and SFFT operation on the time-frequency domain two-dimensional signal to generate a corresponding time delay-Doppler domain receiving signal.
Wherein the performing of the low-complexity MMSE equalization on the received delay-doppler domain signal comprises: performing matrixing on the delay-Doppler domain receiving vector to obtain a delay-Doppler domain receiving signal matrix; performing two-Dimensional Fast Fourier Transform (2D-FFT) on the time delay-Doppler domain received signal, and vectorizing a Transform result; acquiring a channel information characteristic matrix through channel estimation, wherein the channel matrix is a two-dimensional cyclic matrix, namely the channel matrix is a block cyclic matrix firstly, and each block matrix is also a cyclic matrix secondly; calculating the eigenvalue decomposition of the channel matrix according to the channel information eigenvalue matrix to obtain a diagonal matrix of the channel matrix; solving an inverse matrix of the diagonal matrix to obtain a processed channel information inverse matrix; multiplying the processed receiving vector and the processed channel information inverse matrix to obtain a product vector; performing matrixing on the product vector to obtain a product matrix; and performing two-Dimensional Inverse Fast Fourier Transform (2D-IFFT) on the product matrix, vectorizing a Transform result to obtain an equalization result, and outputting the equalization result.
The soft demodulation of the equalization result of each branch to output log-likelihood ratio information, and the calculation of the joint log-likelihood ratio based on the maximum ratio combining method may include: demodulating the equalization result of each branch; and calculating the log-likelihood ratio information of the bit by adopting a soft demodulation method. Merging ideas based on maximum ratio; and summing the log-likelihood ratios of the branches to obtain the maximum ratio combination combined log-likelihood ratio of the branches.
Wherein, the determining the transmission information according to the joint log-likelihood ratio may include: combining the combined log-likelihood ratio according to the bit-level maximum ratio, and judging the corresponding bit to be 0 if the value is positive; combining the combined log-likelihood ratios according to the bit-level maximum ratio, and judging the corresponding bit to be 1 if the value is negative; and outputting a judgment result.
The equalization detection method provided by the embodiment of the invention fully utilizes the dual cycle property of the time delay-Doppler domain channel of the OTFS system, carries out efficient eigenvalue decomposition on the channel matrix through two-dimensional fast Fourier transform (2D-FFT), and further realizes low-complexity linear equalization based on the two-dimensional fast Fourier transform, so that the computational complexity is greatly reduced compared with the conventional OTFS linear equalizer. In addition, based on the soft demodulation and maximum ratio combination method, the maximum ratio combination combined log-likelihood ratio of the multiple branches passing through the beam forming network is calculated, and the spectrum efficiency of the system is fully improved.
Drawings
Fig. 1 is a flow chart of a low complexity signal detection method for a mimo-ofdm system according to some embodiments of the present invention;
fig. 2 is a schematic diagram of a time-varying multipath channel time-frequency domain channel impulse response in accordance with some embodiments of the present invention;
fig. 3 is a schematic diagram of an overall structure of a multiple-input multiple-output-orthogonal time-frequency-space (MIMO-OTFS) system according to some embodiments of the present invention;
fig. 4 is a schematic flow chart of a low complexity signal detection method of a multiple input multiple output-orthogonal time frequency space (MIMO-OTFS) system according to some embodiments of the present invention;
FIG. 5 is a schematic diagram illustrating a comparison of complexity between an equalization detection method according to some embodiments of the present invention and a conventional equalization detection method;
fig. 6 is a schematic diagram comparing bit error rates of an equalization method according to some embodiments of the present invention with a conventional equalization method;
fig. 7 is a diagram of error rate performance of a low complexity detection method for a multiple-input multiple-output-orthogonal time-frequency space (MIMO-OTFS) system according to some embodiments of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to specific embodiments and the accompanying drawings.
Fig. 1 is a design flow chart of a low-complexity signal detection method of a multiple-input multiple-output-orthogonal time-frequency space (MIMO-OTFS) system according to some embodiments of the present invention. As shown in fig. 1, at the receiving end, the receiving signal is formed into a plurality of branches through the antenna array and the beam forming network, and then the delay-doppler domain receiving signal of each branch is obtained and vectorized, so as to obtain the system input-output relationship of the delay-doppler domain vectorization. Further, based on the input-output relation of the delay-Doppler domain vectorization system, a low-complexity Minimum Mean Square Error (MMSE) equalizer is designed, the output of the MMSE equalizer is subjected to soft demodulation, and corresponding log-likelihood ratio (LLR) information is output. And then, performing Maximum Ratio Combining (MRC) on the soft demodulation result of each branch, calculating the joint log-likelihood ratio of all the branches, judging the transmitting information according to the joint log-likelihood ratio, and finally outputting a judgment result.
Fig. 2 is a diagram of the time-frequency domain channel impulse response of a time-varying multipath channel according to some embodiments of the present invention. As shown in fig. 2, the channel varies in both the time and frequency dimensions, reflecting the double-dispersion nature of the channel. In which the time-varying nature of the channel causes inter-subcarrier interference (ICI), which in turn severely impairs the performance of the OFDM system. Therefore, there is a need to research a new multi-carrier modulation technique OTFS capable of effectively resisting doppler frequency offset.
As described above, OTFS modulation, as a novel multi-carrier modulation technique, can effectively combat a highly dynamic communication channel environment, and exhibits strong robustness to channel doppler spread. The MIMO-OTFS system can improve the spectrum efficiency of the system while maintaining the excellent properties.
Fig. 3 is a schematic diagram of an overall structure of a MIMO-OTFS system according to some embodiments of the present invention. As shown in fig. 3, the OTFS system may be implemented by adding a pre/post processing module to the OFDM system. Specifically, the input signal of the transmitting end is a two-dimensional OTFS signal in a time delay-Doppler domain
Figure BDA0002640353870000051
Where M and N are the index values of the delay and doppler dimensions, respectively. Next, the time delay-Doppler domain two-dimensional signal can be converted into a time domain transmission signal through OTFS modulation
Figure BDA0002640353870000052
As shown in the following formula:
Figure BDA0002640353870000053
where x ═ vec (x) is the vectorized OTFS symbol. In addition, ISFFT transform and transmit window function
Figure BDA0002640353870000054
An OTFS pretreatment module is formed; the Inverse Discrete Fourier Transform (IDFT) and Cyclic Prefix (CP) addition operations constitute OFDM modulation, in which,
Figure BDA0002640353870000055
is a CP matrix, and NCPIndicating the length of the CP.
Further, a Uniform Linear Array (ULA) is adopted at the transmitting end, and then the Uniform Linear Array (ULA) is arranged at thetai,qThe Steering vector of the direction (Steering vector) can be expressed as:
Figure BDA0002640353870000056
similarly, the receiving terminal ULA is in the direction vi,qThe steering vector of the direction can be expressed as:
Figure BDA0002640353870000057
the purpose of the beam forming network is to receive incoming signals in a target direction while rejecting signals in other directions. In some embodiments of the invention, a Matched Filter (MF) beamformer is employed. Thus, the transmitting end and the receiving end are in the direction θkAnd
Figure BDA0002640353870000058
the beamforming vectors of (a) may be represented as:
Figure BDA0002640353870000059
Figure BDA00026403538700000510
wherein N istAnd NrThe antenna array numbers of the transmitting end and the receiving end are respectively, and K is 1, …, K-1, L is 1, … and L-1.
Further, after the transmitted symbol in equation (1) passes through the time-varying multipath channel, the time-domain received signal of the l-th branch can be represented as:
Figure BDA0002640353870000061
wherein
Figure BDA0002640353870000062
Is an additive white gaussian noise matrix.
Based on the time domain received signal, obtaining a corresponding time delay-Doppler domain received signal through OTFS inverse transformation:
Figure BDA0002640353870000063
wherein the CP removal operation and Discrete Fourier Transform (DFT) constitute an OFDM demodulation module. Receive window function
Figure BDA0002640353870000064
And SFFT transformation to form an OTFS post-processing module.
And then, the delay-Doppler domain receiving symbol of each branch passes through the low-complexity signal detection method provided by the invention, and a final symbol judgment result is output.
Fig. 4 is a schematic flow chart of a low-complexity signal detection method of a multiple-input multiple-output-orthogonal time-frequency space (MIMO-OTFS) system according to some embodiments of the present invention. As shown in fig. 4, the signal demodulated by the OTFS on the l-th receiving branch is obtained first, that is, equation (7) can be further expressed as:
Figure BDA0002640353870000065
wherein
Figure BDA0002640353870000066
In addition, in the embodiment of the present invention, the channel matrix H is a dual cyclic matrix, i.e. the sub-matrices of the channel matrix H exhibit block cyclic property, wherein each sub-matrix is a cyclic matrix. In the following description of the present invention, the branch indices l are omitted for clarity of presentation.
The specific structure of the channel matrix H is shown in formula (9)
Figure BDA0002640353870000067
Wherein H0、H1、…、HM-2And HM-1Are all the above-mentioned lettersThe channel matrix H is a sub-matrix and is a circulant matrix.
After obtaining the delay-doppler domain received signal vector, we design a low complexity MMSE equalization method for the signal, as shown in fig. 4. It is known that a dual circulant matrix can be diagonalized by a Two-Dimensional Discrete Fourier Transform (2D-DFT) matrix. Considering that FFT is a fast algorithm for implementing DFT, the embodiment of the present invention performs eigenvalue decomposition on the channel matrix H with dual cycle property by using two-dimensional fast fourier transform (2D-FFT), so as to implement diagonalization on the channel matrix H, and the diagonalization process may only use any row or any column of the channel matrix H.
The low complexity MMSE equalization method employed in the embodiments of the present invention will be described in detail below.
Defining the 2D-DFT matrix and the 2D-IDFT matrix as shown in equations (10) and (11), respectively:
Figure BDA0002640353870000071
Figure BDA0002640353870000072
wherein, FMRepresenting an M-point DFT matrix.
Further, the column vectors of the two-dimensional NM × NM IDFT matrix are eigenvectors of the corresponding NM × NM dual cyclic matrix, so the dual cyclic channel matrix H has the following eigenvalue decomposition:
H＝Ξ-1ΔΞ (12)
where Δ is a diagonal matrix whose diagonal elements are eigenvalues of matrix H.
In eigenvalue decomposition of the channel matrix, i.e. equation (12), the diagonal matrix may be obtained only through the first column of the channel matrix H, specifically
Δ＝diag(vec(FNH'FM)) (13)
Wherein, diag (a) operation indicates that a diagonal matrix is formed by using elements of the vector a, and vec (a) operation indicates vectorization of the matrix a. In addition, it should be noted that H' is a matrix formed by the first column of the channel matrix H, that is, the proposed scheme can obtain the eigenvalue decomposition of the channel matrix only through the first column of the channel matrix.
Note that fast fourier transform FFT) is a fast algorithm for Discrete Fourier Transform (DFT), so we propose to efficiently implement two-dimensional discrete fourier transform (2D-DFT) with two-dimensional fast fourier transform (2D-FFT). Here, we define a new operator:
Figure BDA0002640353870000081
the operation operator mainly comprises two steps: firstly, performing 2D-FFT operation on a matrix A, specifically, performing FFT operation on all columns of the matrix A, and then performing FFT operation on all rows of the obtained new matrix; secondly, vectorizing the result obtained in the first step.
Based on equations (13) and (14), it can be seen that the diagonal matrix Δ obtained by decomposing the eigenvalues of the dual circulant matrix H can be obtained by 2D-FFT transformation only through the first column of H:
Δ＝diag(vFFT2(H')) (15)
through the aforementioned dual cycle characteristic of the delay-doppler domain channel and the characteristic value decomposition of the channel matrix based on 2D-FFT, we further propose a low-complexity MMSE equalizer based on 2D-FFT, which is described in detail below.
Substituting the eigenvalue decomposition of H, equation (12), into the vectorized system output-output relationship model (i.e., equation (8)), can obtain another representation of the system input-output relationship:
y＝Ξ-1ΔΞx+z (16)
further, the output of the proposed low complexity Minimum Mean Square Error (MMSE) equalizer can be expressed as:
Figure BDA0002640353870000082
wherein y is the receiving sequence of a branch in the delay-Doppler domain at the receiving end, and operation unwec (a) is the inverse operation of vec (A),
Figure BDA0002640353870000083
as a variance of the noise, INMIs a unit matrix of NM × NM.
Further, as shown in fig. 4, after the output of the low complexity MMSE equalizer is obtained, the corresponding log-likelihood ratio information is calculated by the soft demodulation unit, which will be described in detail as follows.
For the time delay-doppler domain transmit information x ═ x in equation (1)1,x2,…,xNM]TEach symbol of which is modulated by a bit sequence of length Q, defined here as at＝[at,1,at,2,…,at,Q]TWhere t represents the tth transmitted symbol xt. Then the low complexity MMSE equalization output of the l-th branch is obtained
Figure BDA0002640353870000084
After that, bit at,q′The Log-Likelihood Ratio (Log-likehood Ratio) of Q' 1, … can be expressed as:
Figure BDA0002640353870000091
wherein
Figure BDA0002640353870000092
Represents a subset of q' bits taking 0(1)
Figure BDA0002640353870000093
Further, after obtaining the log-likelihood ratios of the branches as shown in fig. 4, the present invention combines the log-likelihood ratios of the branches by a Maximum Ratio Combining (MRC) method to obtain a joint log-likelihood ratio of the branches, and the correlation operation is as shown in equation (19):
Figure BDA0002640353870000094
next, the transmitted information is decided according to the maximum ratio combining joint log-likelihood ratio, as shown in equation (20):
Figure BDA0002640353870000095
and finally, outputting the judgment result of the transmitted information.
To demonstrate the performance of various embodiments of the present invention, the inventors performed multiple monte carlo simulation tests. Fig. 5, 6 and 7 show the results of the simulation test. Fig. 5 is a schematic diagram illustrating a complexity comparison between a low-complexity Minimum Mean Square Error (MMSE) linear equalization scheme according to some embodiments of the present invention and other existing linear equalization schemes; fig. 6 is a schematic diagram illustrating the error rate performance of an OTFS system based on an improved Minimum Mean Square Error (MMSE) linear equalization scheme, the error rate performance of an OTFS system based on other linear equalization schemes, and the error rate performance of a conventional OFDM system in a high dynamic scenario according to some embodiments of the present invention; fig. 7 is a schematic diagram illustrating the error rate performance comparison of the MIMO-OTFS system based on the improved complexity MMSE-MRC signal detection method under different antenna number configurations.
The simulation experiment shown in fig. 5 uses the number of complex multiplications involved in the equalization process as a measure, and gives a comparison between the FFT2-MMSE equalization method proposed in the embodiment of the present invention and the complexity of the other two linear equalizers. The first comparison scheme is traditional MMSE equalization based on matrix inversion, and the second comparison scheme is frequency domain ZF equalization based on a kronecker product. As can be seen from fig. 5, the complexity of the linear equalization method provided by the embodiment of the present invention is far lower than that of the linear equalizer of the existing OTFS system.
The simulation experiment shown in fig. 6 shows that the FFT proposed in the embodiment of the present invention is performed in a high dynamic scenario2The MMSE equalization method compares the bit error rate with the other two linear equalizers. Wherein the first comparison scheme is based onCompared with the error rate of the conventional matrix-inverted MMSE-equalized OFDM system, the second comparison scheme is the error rate of the conventional matrix-inverted MMSE-equalized OTFS system, and as can be seen from fig. 6, compared with the conventional OFDM system, the error rate performance of the OTFS system has obvious advantages in a high-dynamic scene. And secondly, compared with the existing linear equalizer of the OTFS system, the linear equalization method provided by the invention has no loss on the bit error rate performance.
Fig. 7 shows a bit error rate performance diagram of the low-complexity MMSE-MRC signal detection scheme provided in the embodiment of the present invention for a MIMO-OTFS system configured with different antenna numbers. The three schemes respectively test the error rate performance of 1 × 1, 2 × 2 and 3 × 3MIMO-OTFS systems. As can be seen from fig. 7, based on the improved MMSE-MRC detection method, the MIMO-OTFS has strong robustness to a high dynamic scene, and simultaneously obtains good spectral efficiency.
While the present invention has been described in conjunction with specific embodiments thereof, many alternatives, modifications, and variations of these embodiments will be apparent to those of ordinary skill in the art in light of the foregoing description. For example, the discussed embodiments may be used in other antenna count configurations and channel conditions, etc.
The embodiments of the invention are intended to embrace all such alternatives, modifications and variances that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, substitutions, improvements and the like that may be made without departing from the spirit and principles of the invention are intended to be included within the scope of the invention.

Claims (9)

1. A low complexity signal detection method for MIMO-OFDM system, the method comprising:
the transmitting terminal transmits Orthogonal Time Frequency Space (OTFS) signals through a transmitting antenna array and a beam forming network;
the transmitting signal passes through a time-varying multipath channel to obtain a time domain receiving signal;
forming time domain receiving signals of a plurality of branches for the time domain receiving signals through a receiving antenna array and a beam forming network;
forming the time delay of the multiple branches by passing the time domain received signals of the multiple branches through an OTFS demodulation module
-receiving a signal in the doppler domain;
performing low complexity Minimum Mean Square Error (MMSE) equalization on the delay-Doppler domain received signal,
outputting an equalization result;
performing soft demodulation on the equalization result of each branch, and outputting log-likelihood ratio information (LLR);
performing combined log-likelihood ratio calculation on the log-likelihood ratio information of each branch based on a Maximum Ratio Combining (MRC) method;
and judging the transmission information according to the combined log-likelihood ratio, and outputting a judgment result.
2. The method of claim 1, wherein the OTFS transmit signal comprises:
performing Inverse Sine Finite Fourier Transform (ISFFT) and windowing operation on a two-dimensional signal generated in a time delay-Doppler domain to obtain a corresponding time-frequency domain two-dimensional signal;
and performing orthogonal frequency division multiple access (OFDM) modulation on the time-frequency domain two-dimensional signal to generate a time domain transmitting signal.
3. The method of claim 1, wherein the time-varying multipath channel comprises:
time-varying channel caused by relative motion of the transceiving ends; and
doppler frequency offset and inter-subcarrier interference (ICI) due to channel time-variability;
multiple propagation paths caused by reflectors in the channel; and
channel delay and intersymbol interference (ISI) caused by multiple propagation paths.
4. The method of claim 1, wherein the receive antenna array and the beam forming network comprise:
the time domain signal reaching the receiving end comprises incoming waves of all azimuth angles of a channel;
the beam forming network only receives the incoming waves in the target direction, and suppresses the incoming waves in other directions.
5. The method of claim 1, wherein the performing orthogonal time-frequency-space demodulation on the received signal of each branch to obtain the received signal of each branch in the delay-doppler domain comprises:
OFDM demodulation is carried out on the received time domain signals of each branch, and time-frequency domain two-dimensional signals are generated;
and performing windowing and Sharp Finite Fourier Transform (SFFT) on the time-frequency domain two-dimensional signal to generate a corresponding time delay-Doppler domain two-dimensional receiving signal.
6. The method of claim 1, wherein the low complexity MMSE equalization of the received delay-doppler domain signal comprises:
performing matrixing on the delay-Doppler domain receiving vector to obtain a delay-Doppler domain receiving signal matrix;
2D-FFT is carried out on the received signal of the time delay-Doppler domain, and the vectorization is carried out on the transformation result;
acquiring a channel information characteristic matrix through channel estimation, wherein the channel matrix is a two-dimensional cyclic matrix, namely the channel matrix is a block cyclic matrix firstly, and each block matrix is also a cyclic matrix secondly;
calculating the eigenvalue decomposition of the channel matrix according to the channel information eigenvalue matrix to obtain a diagonal matrix of the channel matrix;
solving an inverse matrix of the diagonal matrix to obtain a processed channel information inverse matrix;
multiplying the processed receiving vector and the processed channel information inverse matrix to obtain a product vector;
performing matrixing on the product vector to obtain a product matrix; and
and performing two-dimensional inverse fast Fourier transform (2D-IFFT) on the product matrix, vectorizing a transformation result to obtain an equalization result, and outputting the equalization result.
7. The method of claim 1, wherein the soft demodulating the equalization result of each branch and outputting log-likelihood ratio information comprises:
demodulating the equalization result of each branch;
and calculating the log likelihood ratio information of the bit level by adopting a soft demodulation method.
8. The method of claim 1, wherein the performing the joint log-likelihood ratio calculation based on the maximum ratio combining method for each branch log-likelihood ratio information comprises:
merging ideas based on maximum ratio;
and summing the log-likelihood ratios of the branches to obtain the combined log-likelihood ratio of the branches.
9. The method of claim 1, wherein the determining the transmitted information based on the joint log-likelihood ratio comprises:
combining the combined log-likelihood ratios according to the bit-level maximum ratio, and judging the corresponding bit to be 0 if the value is positive;
combining the combined log-likelihood ratios according to the bit-level maximum ratio, and judging the corresponding bit to be 1 if the value is negative;
and outputting a judgment result.
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