CN113364535A - Method, system, device and storage medium for mathematical form multiple-input multiple-output detection - Google Patents
Method, system, device and storage medium for mathematical form multiple-input multiple-output detection Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
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- 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
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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Abstract
The invention discloses a mathematical form multiple input multiple output detection method, a system, equipment and a storage medium, comprising the following steps: acquiring a channel matrix, and acquiring a sample space division matrix W according to the channel matrix; dividing a matrix W through a sample space to obtain a mapping matrix V; when a received signal is input, the received signal is processed by a sample space division matrix W and then processed by a mapping matrix V to estimate and obtain a transmitting signal.
Description
Technical Field
The invention belongs to the technical field of signal detection, and relates to a mathematical form multiple-input multiple-output detection method, a mathematical form multiple-input multiple-output detection system, mathematical form multiple-input multiple-output detection equipment and a mathematical form multiple-input multiple-output detection storage medium.
Background
Mobile communication has been developed over the last several decades, and wireless communication technology has now been deeply involved in life, and has now begun to truly change people's lives. From the portable telephone which is heavy at first to the smart phone which is one hand of people at present, simple voice communication cannot meet the requirements of people, software such as games, music, videos and the like are numerous, great convenience is brought to daily activities of people, and the development of the mobile communication technology is relied on.
Communication systems are constantly evolving, now from first generation mobile communication systems to fourth generation mobile communication systems. Studies of 5G have been carried out. With the rapid development of the internet, the number of terminals and the demand of users have increased greatly, and the existing fourth generation mobile communication system has not been able to meet the demand of people in the future, and in this background, people develop a fifth generation mobile communication system. The fifth generation mobile communication system aims at high speed, low time delay and mass access, so that the realization of the interconnection of everything is expected, and the realization of 5G comprehensive commercial is primarily determined in 2020. 5G provides people with a lot of convenience and contributes to the society. The fifth generation mobile communication system defines three typical application scenarios, namely enhanced mobile broadband (eMBB), ultra-high reliability low-delay communication (URLLC), and communication with massive machine nodes (mMTC). To achieve these goals, 5G introduces massive MIMO technology, and uses higher-order modulation modes, such as 64QAM modulation and 128QAM modulation, while using higher-order MIMO. Meanwhile, 5G also adopts more novel coding techniques, which enable faster transmission rate and larger system capacity. The mass machine nodes are mainly medium and low-end communication equipment. With the development of communication systems, the MIMO order of middle and low end communication devices will also increase, reaching 2 × 2 and 4 × 4. Even under the MIMO order, the complexity of the maximum likelihood algorithm is still high and cannot be applied to the practice, and although the performance of the classical sphere decoding algorithm and the breadth-first tree searching algorithm approaches the maximum likelihood algorithm, and the complexity is slightly reduced compared with the maximum likelihood algorithm, the complexity is still a little expense. Although the complexity of linear detection algorithms with low complexity, such as a minimum mean square error algorithm and a zero forcing algorithm, is low, the detection performance is greatly reduced, and a detection algorithm which gives consideration to both the detection performance and the complexity is urgently needed at present.
Disclosure of Invention
The present invention is directed to overcome the above-mentioned shortcomings in the prior art, and provides a mathematical multiple-input multiple-output detection method, system, device and storage medium, which can effectively reduce the complexity of detection and have high detection performance.
In order to achieve the above object, the method for detecting multiple inputs and multiple outputs in mathematical form according to the present invention comprises:
acquiring a channel matrix, and acquiring a sample space division matrix W according to the channel matrix;
dividing a matrix W through a sample space to obtain a mapping matrix V;
when a received signal is input, the received signal is processed by a sample space division matrix W and then processed by a mapping matrix V to obtain a transmitting signal by estimation.
Further comprising:
when the channel changes, the sample space division matrix W and the mapping matrix V are obtained according to the channel matrix again.
The specific process of obtaining the sample space division matrix W according to the channel matrix is as follows:
generating a transmitting constellation point set x according to a channel matrix H and a modulation mode of a signalzAnd receiving a constellation point set Hxz；
According to the received constellation point set HxzSearching 50 adjacent receiving constellation points of each receiving constellation point;
solving a vertical bisector of each receiving constellation point and 50 adjacent receiving constellation points;
and removing repeated vertical bisectors, and constructing a sample space division matrix W through the remaining vertical bisectors.
The specific process of obtaining the mapping matrix V by dividing the matrix W through the sample space is as follows:
substituting the two receiving constellation points which generate the vertical bisector into the vertical bisector;
processing the vertical bisector through a sign function to enable the vertical bisector to tend to be +1 or-1;
and storing the vertical bisector processed by the symbolic function into a mapping matrix V, and storing the mapping matrix V in a sparse matrix form.
When a received signal is input, the received signal is processed by a sample space division matrix W, and then is processed by a mapping matrix V, so that the specific process of estimating and obtaining the transmitting signal is as follows:
when a received signal is input, carrying out matrix multiplication operation on the received signal and a sample space division matrix W; obtaining yW;
processing the yW through a sign function to obtain sgn (yW);
carrying out matrix multiplication on sgn (yW) and a mapping matrix V to obtain sgn (yW) multiplied by V;
performing matrix division operation on sgn (yW) xV to obtain sgn (yW) xV/sum (V);
and selecting the index of the maximum value in sgn (yW) multiplied by V/sum (V) as a transmitting signal for estimation and output.
When the channel matrix changes, regenerating a sample space division matrix W;
when the channel matrix changes, regenerating a mapping matrix V;
when the channel matrix changes, the received signal is detected again.
A mathematical form multiple-input multiple-output detection system comprising:
the first processing module is used for acquiring a channel matrix and obtaining a sample space division matrix W according to the channel matrix;
the second processing module is used for dividing the matrix W through a sample space to obtain a mapping matrix V;
and the estimation module is used for processing the received signal by a sample space division matrix W when the received signal is input and then by a mapping matrix V to estimate and obtain a transmitting signal.
A computer device comprising a memory, a processor and a computer program stored in said memory and executable on said processor, said processor implementing the steps of said method of mathematical form multiple-input multiple-output detection when executing said computer program.
A computer-readable storage medium, storing a computer program which, when executed by a processor, implements the steps of the mathematical form multiple-input multiple-output detection method.
The invention has the following beneficial effects:
when the method, the system, the equipment and the storage medium for detecting the multiple inputs and the multiple outputs in the mathematical form are specifically operated, the received signals are sequentially processed by the sample space division matrix W and the mapping matrix V to estimate and obtain the transmitted signals, so that the detection of the received signals is realized, the operation is simple and convenient, and the detection complexity is low. Through simulation experiments, compared with the traditional MIMO detection algorithm, the method has the advantages of excellent error rate and execution time, namely excellent detection performance.
Drawings
FIG. 1 is a schematic diagram of a sample space partition matrix W and a mapping matrix V according to the present invention;
FIG. 2 is a schematic diagram illustrating detection when a received signal is input in the present invention;
fig. 3 is a schematic diagram of the bit error rate of the time-varying channel in the 4 × 4MIMO and QPSK modulation modes according to various simulation algorithms in the present application.
Detailed Description
The present invention will be described in detail below with reference to the embodiments with reference to the attached drawings. It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict.
The following detailed description is exemplary in nature and is intended to provide further details of the invention. Unless otherwise defined, all technical terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the invention.
The MIMO (Multiple-Input Multiple-Output) technology described in the present invention is to use Multiple transmitting antennas and Multiple receiving antennas at the transmitting end and the receiving end, respectively, so that signals are transmitted and received through the Multiple antennas at the transmitting end and the receiving end, thereby improving communication quality, and then making full use of space resources, and achieving Multiple transmission and Multiple reception through the Multiple antennas, and increasing system channel capacity by Multiple times without increasing spectrum resources and antenna transmission power, and a large-scale MIMO (Multiple-Input Multiple-Output) technology is regarded as the most promising technology in the 5G (5th-Generation, fifth-Generation mobile communication technology) physical layer.
Example one
Referring to fig. 1 and 2, the method for detecting multiple inputs and multiple outputs in mathematical form according to the present invention includes the following steps:
1) obtaining a sample space division matrix W according to the channel matrix;
the specific operation process of the step 1) is as follows:
1a) generating a transmitting constellation point set x according to a channel matrix H and a modulation mode of a signalzAnd receiving a constellation point set Hx2；
1b) According to the received constellation point set HxzSearching 50 adjacent receiving constellation points of each receiving constellation point;
1c) solving the perpendicular bisector of each received constellation point and its neighboring 50 received constellation points, i.e. q ═ xz1-xz2,q0＝-0.5(xz1-xz2)T(xz1+xz2)；
1d) Removing repeated vertical bisectors, and constructing a sample space division matrix W through the remaining vertical bisectors, wherein the size of the sample space division matrix W is Nt×M。
2) Dividing a matrix W through a sample space to obtain a mapping matrix V;
the specific operation process of the step 2) is as follows:
2a) substituting the two receiving constellation points which generate the vertical bisector into the vertical bisector;
2b) processing the vertical bisector through a sign function to enable the vertical bisector to tend to be +1 or-1;
2c) and storing the vertical bisectors processed by the symbol function into a mapping matrix V, and storing the mapping matrix V in a sparse matrix form, wherein the size of the mapping matrix V is M multiplied by N, M is the number of the perpendicular bisectors, N is the number of the receiving constellation points, and the initial values are all 0.
3) When a received signal is input, the received signal is processed by a sample space division matrix W and then is processed by a mapping matrix V to obtain a transmitting signal by estimation;
the specific operation process of the step 3) is as follows:
3a) when a received signal is input, carrying out matrix multiplication operation on the received signal and a sample space division matrix W; obtaining yW;
3b) processing the yW through a sign function to obtain sgn (yW);
3c) carrying out matrix multiplication on sgn (yW) and a mapping matrix V to obtain sgn (yW) multiplied by V;
3d) performing matrix division operation on sgn (yW) xV to obtain sgn (yW) xV/sum (V);
3e) and selecting the index of the maximum value in sgn (yW) multiplied by V/sum (V) as a transmitting signal for estimation and output.
4) When the channel changes, obtaining a sample space division matrix W and a mapping matrix V again according to the channel matrix;
the specific operation process of the step 4) is as follows:
regenerating a sample space division matrix W when the channel matrix changes, the size of the sample space division matrix W being Nt×M；
When the channel matrix changes, regenerating a mapping matrix V, wherein the size of the mapping matrix V is MXN;
when the channel matrix changes, the received signal is detected again.
Verification experiment
The invention is compared with a maximum likelihood detection algorithm and a minimum mean square error detection algorithm on two dimensions of detection performance and complexity, and the specific process is as follows:
respectively simulating and realizing a maximum likelihood detection algorithm and a minimum mean square error algorithm in the traditional detection algorithm;
the invention is realized by simulation;
the maximum likelihood detection algorithm, the minimum mean square error algorithm and the method are compared in the aspect of execution time by adopting the same test set.
Specifically, on a windows system MATLAB platform, a maximum likelihood detection algorithm, a minimum mean square error algorithm and the method are respectively realized in a simulation mode; the same test set is generated when the signal-to-noise ratio is 0dB-20dB, the test set is used for testing the execution time of the algorithm, and table 1 shows the execution time of various simulation algorithms in a 4 × 4MIMO, QPSK modulation mode for time-varying channels.
Watch (A)
| Detection algorithm | Maximum likelihood detection algorithm | Minimum mean square error algorithm | Mathematical form detection algorithm |
| Execution time | 0.0175 | 0.0052 | 0.0145 |
Example two
A mathematical form multiple-input multiple-output detection system comprising:
the first processing module is used for acquiring a channel matrix and obtaining a sample space division matrix W according to the channel matrix;
the second processing module is used for dividing the matrix W through a sample space to obtain a mapping matrix V;
and the estimation module is used for processing the received signal by a sample space division matrix W when the received signal is input and then by a mapping matrix V to estimate and obtain a transmitting signal.
EXAMPLE III
A computer device comprising a memory, a processor and a computer program stored in said memory and executable on said processor, said processor implementing the steps of said method of mathematical form multiple-input multiple-output detection when executing said computer program.
Example four
A computer-readable storage medium, storing a computer program which, when executed by a processor, implements the steps of the mathematical form multiple-input multiple-output detection method.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting the same, and although the present invention is described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications and equivalents may be made to the embodiments of the invention without departing from the spirit and scope of the invention, which is to be covered by the claims.
Claims (9)
1. A mathematical form multiple-input multiple-output detection method, comprising:
acquiring a channel matrix, and acquiring a sample space division matrix W according to the channel matrix;
dividing a matrix W through a sample space to obtain a mapping matrix V;
when a received signal is input, the received signal is processed by a sample space division matrix W and then processed by a mapping matrix V to obtain a transmitting signal by estimation.
2. The method of mathematical form multiple-input multiple-output detection according to claim 1, further comprising:
when the channel changes, the sample space division matrix W and the mapping matrix V are obtained according to the channel matrix again.
3. The method of claim 1, wherein the specific process of obtaining the sample space division matrix W according to the channel matrix is as follows:
generating a transmitting constellation point set x according to a channel matrix H and a modulation mode of a signalzAnd receiving a constellation point set Hxz；
According to the received constellation point set HxzFinding each receiving star50 receiving constellation points with adjacent seat points;
solving a vertical bisector of each receiving constellation point and 50 adjacent receiving constellation points;
and removing repeated vertical bisectors, and constructing a sample space division matrix W through the remaining vertical bisectors.
4. The method according to claim 1, wherein the specific process of obtaining the mapping matrix V by dividing the matrix W by the sample space is as follows:
substituting the two receiving constellation points which generate the vertical bisector into the vertical bisector;
processing the vertical bisector through a sign function to enable the vertical bisector to tend to be +1 or-1;
and storing the vertical bisector processed by the symbolic function into a mapping matrix V, and storing the mapping matrix V in a sparse matrix form.
5. The method as claimed in claim 1, wherein when a received signal is input, the received signal is processed by a sample space division matrix W, and then processed by a mapping matrix V, so as to obtain the transmitted signal by estimation:
when a received signal is input, carrying out matrix multiplication operation on the received signal and a sample space division matrix W; obtaining yW;
processing the yW through a sign function to obtain sgn (yW);
carrying out matrix multiplication on sgn (yW) and a mapping matrix V to obtain sgn (yW) multiplied by V;
performing matrix division operation on sgn (yW) xV to obtain sgn (yW) xV/sum (V);
and selecting the index of the maximum value in sgn (yW) multiplied by V/sum (V) as a transmitting signal for estimation and output.
6. The method of claim 1, wherein the sample space division matrix W is regenerated when the channel matrix changes;
when the channel matrix changes, regenerating a mapping matrix V;
when the channel matrix changes, the received signal is detected again.
7. A mathematical form multiple-input multiple-output detection system, comprising:
the first processing module is used for acquiring a channel matrix and obtaining a sample space division matrix W according to the channel matrix;
the second processing module is used for dividing the matrix W through a sample space to obtain a mapping matrix V;
and the estimation module is used for processing the received signal by a sample space division matrix W when the received signal is input and then by a mapping matrix V to estimate and obtain a transmitting signal.
8. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the steps of the method of mathematical form multiple-input multiple-output detection as claimed in any one of claims 1 to 6 when executing the computer program.
9. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the method of mathematical form multiple-input multiple-output detection according to any one of claims 1 to 6.
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