Hybrid MIMO detection method and device, electronic equipment and storage medium
By employing a hybrid MIMO detection method, utilizing singular value decomposition and zero-forcing detection techniques, the signal detection problem of MIMO systems under harsh environments was solved, achieving signal recovery with low complexity and low bit error rate under ill-conditioned channel conditions.
Patent Information
- Application Number
- CN202511123193.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-08-12
- Publication Date
- 2025-11-18
AI Technical Summary
In harsh communication environments, the performance of signal detection algorithms in MIMO systems degrades, especially under ill-conditioned channel conditions where the bit error rate is high and traditional detection algorithms fail.
A hybrid MIMO detection method is adopted, which discards singular values and corresponding eigenvectors that are less than the preset conditions through singular value decomposition, reconstructs the channel matrix, and iterates the signal detection one by one through zero-forcing detection and quantization decision to reduce the impact of noise and signal aliasing.
In line-of-sight propagation and close antenna spacing, it effectively reduces noise impact, decreases bit error rate, and improves signal detection accuracy.
Smart Images
Figure CN120979575A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of wireless communication signal detection technology, and specifically to a hybrid MIMO detection method, apparatus, electronic device, and storage medium. Background Technology
[0002] Air-to-ground links between swarm drones, accompanying jammers, and ground stations typically have fewer scattering and reflection components, primarily dominated by line-of-sight (LOS) propagation, resulting in strong correlation between antennas in the antenna array. This correlation weakens the performance of MIMO communication systems, especially in harsh emergency environments such as battlefields where communication conditions are even more demanding. To separate the aliased transmitted signals from the noisy received signals, the receiver must employ effective detection methods.
[0003] However, when the channel matrix becomes ill-conditioned, traditional linear and nonlinear detection algorithms either become too complex or only applicable in certain ideal scenarios, resulting in excessively high bit error rates and extreme sensitivity to channel matrix errors. The performance of traditional detection algorithms deteriorates sharply or even fails completely under ill-conditioned conditions.
[0004] Therefore, how to achieve signal detection under harsh communication conditions is an urgent problem to be solved. Summary of the Invention
[0005] In view of the above problems, the present invention provides a hybrid MIMO detection method, apparatus, electronic device and storage medium, which can reduce the impact of noise on the signal and reduce the bit error rate under harsh channel conditions.
[0006] In a first aspect, embodiments of the present invention provide a hybrid MIMO detection method, the hybrid MIMO detection method comprising: S110: Obtain the channel matrix, matrix dimension, truncation factor, and received signal, wherein the matrix dimension is used to set the maximum number of iterations; S120: Perform singular value decomposition on the channel matrix, and discard singular values and corresponding eigenvectors that are less than a preset condition according to the truncation factor to obtain the reconstructed channel matrix; S130: Calculate the pseudo-inverse of the reconstructed channel matrix and obtain the estimated value of the current path signal through zero-forcing detection; S140: After quantizing and deciding the estimated value, eliminate the current path interference from the received signal and update the received signal; S150: Set the corresponding column in the channel matrix to zero, proceed to the next signal detection, and repeat steps S110 to S140 until the maximum number of iterations is reached and the detection result is output.
[0007] In some embodiments, the expression for discarding the preset condition of singular values includes:
[0008] In the formula, For the maximum singular value, For the first A singular value, This is the cutoff factor.
[0009] In some embodiments, the expression for performing singular value decomposition on the channel matrix includes:
[0010] In the formula, For the channel matrix, It is a left singular matrix. It is a singular value diagonal matrix. It is a right singular matrix.
[0011] In some embodiments, obtaining the estimated value of the current path signal through zero-forcing detection includes: The estimated value of the current path signal is obtained using the first calculation formula, which is:
[0012] In the formula, Let be the estimated value of the nth signal, and A be the pseudo-inverse of the reconstructed channel matrix. This is the nth row of the pseudo-inverse A, where Data is the current received signal.
[0013] In some embodiments, the quantization decision is a demodulation decision based on QPSK modulation.
[0014] In some embodiments, the hybrid MIMO detection method further includes a preprocessing step, specifically: The input signals are QPSK modulated and mapped onto the transmitting antenna for transmission. The transmitting signal propagates to the receiving end via a line-of-sight channel. The receiving end simulates channel fading through a signal amplifier and performs signal detection using the method described in claim 1. The detected signal is demodulated, and the estimated signal value is output.
[0015] In some embodiments, the hybrid MIMO detection method further includes: reconstructing the channel matrix, the expression of which is:
[0016] In the formula, The truncated left singular matrix, This is the truncated singular value diagonal matrix. This is the truncated right singular matrix. This indicates a truncated singular value decomposition.
[0017] Secondly, embodiments of the present invention provide a hybrid MIMO detection device, the hybrid MIMO detection device comprising: The acquisition module is used to acquire the channel matrix, matrix dimension, truncation factor, and received signal, wherein the matrix dimension is used to set the maximum number of iterations; The reconstruction module is used to perform singular value decomposition on the channel matrix and discard singular values and corresponding eigenvectors that are less than a preset condition according to the truncation factor to obtain the reconstructed channel matrix. The detection module is used to obtain the pseudo-inverse of the reconstructed channel matrix and to obtain the estimated value of the current path signal through zero-forcing detection. The update module is used to quantize and decide the estimated value, eliminate the current path interference from the received signal, and update the received signal. The output module is used to set the corresponding column in the channel matrix to zero, proceed to the next signal detection, and repeat steps S110 to S140 until the number of iterations reaches the maximum number of iterations and output the detection result.
[0018] Thirdly, embodiments of this application provide an electronic device, including a memory and a processor, wherein the memory stores program code that can run on the processor, and when the program code is executed by the processor, it implements a hybrid MIMO detection method as described in any embodiment of the first aspect.
[0019] Fourthly, embodiments of this application provide a computer storage medium storing one or more programs, which can be executed by an electronic device as described in the third aspect to implement a hybrid MIMO detection method as described in any embodiment of the first aspect.
[0020] This invention provides a hybrid MIMO detection method, apparatus, electronic device, and storage medium, comprising: acquiring a channel matrix, matrix dimension, truncation factor, and receiver signal; wherein the matrix dimension is used to set the maximum number of iterations; performing singular value decomposition on the channel matrix; discarding singular values and corresponding eigenvectors less than a preset condition according to the truncation factor to obtain a reconstructed channel matrix; obtaining a pseudo-inverse of the reconstructed channel matrix; obtaining an estimate of the current path signal through zero-forcing detection; quantizing and deciding the estimate to eliminate current path interference from the receiver signal; updating the receiver signal; setting the corresponding column in the channel matrix to zero; proceeding to the next path signal detection; repeating the above steps until the number of iterations reaches the maximum number of iterations and outputting the detection result. In transmission links with fewer scattering and reflection components and with very close antenna spacing, this method reduces the impact of noise on the signal and solves the signal aliasing problem.
[0021] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description
[0022] The invention will now be described in more detail with reference to embodiments and the accompanying drawings.
[0023] Figure 1 This diagram illustrates an exemplary hybrid MIMO detection method according to an embodiment of the present invention. Figure 2 The diagram illustrates a processing flowchart of a hybrid MIMO detection method that combines a truncated singular value zero-forcing detection algorithm with an interference cancellation algorithm in an exemplary embodiment of the present invention. Figure 3 A schematic diagram of the model structure of an exemplary LOS MIMO system proposed in one embodiment of the present invention is shown; Figure 4 A structural block diagram of a hybrid MIMO detection device according to an embodiment of the present invention is shown; Figure 5 This paper shows a structural block diagram of an electronic device for performing a hybrid MIMO detection method according to an embodiment of this application. Figure 6 A computer-readable storage medium for storing or carrying a hybrid MIMO detection method according to an embodiment of this application is shown. Detailed Implementation
[0024] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the embodiments and accompanying drawings. The illustrative embodiments and descriptions of the present invention are only used to explain the present invention and are not intended to limit the present invention.
[0025] In existing technologies, when the channel matrix is ill-conditioned, traditional linear and nonlinear detection algorithms either have excessively high complexity or are only applicable in some ideal situations, resulting in excessively high bit error rates and extreme sensitivity to channel matrix errors. The performance of traditional detection algorithms degrades sharply or even fails completely under ill-conditioned conditions.
[0026] To address the aforementioned issues, the applicant proposes a hybrid MIMO detection method, apparatus, electronic device, and storage medium, which is an effective detection algorithm that remains efficient even under ill-conditions, has low complexity, and meets communication requirements in terms of bit error rate. This hybrid MIMO detection method, even in transmission links with few scattering and reflection components and with very close antenna spacing, reduces the impact of noise on the signal and solves the signal aliasing problem. The performance of this method is superior to traditional detection methods.
[0027] One of the hybrid MIMO detection methods will be described in detail in the following embodiments.
[0028] The following describes an application scenario of a hybrid MIMO detection method provided by an embodiment of the present invention: Please see Figure 1 , Figure 1 This is a schematic diagram of a hybrid MIMO detection method provided in an embodiment of the present invention. In this embodiment, a hybrid MIMO detection method can be applied to, for example... Figure 4 The hybrid MIMO detection device 300 shown is... Figure 5 The electronic device 200 shown and Figure 3 The diagram shows a model structure of a LOSMIMO system. The following section discusses... Figure 1 The process shown is described in detail. A hybrid MIMO detection method may include steps S110 to S150.
[0029] S110: Obtain the channel matrix, matrix dimension, truncation factor, and received signal, wherein the matrix dimension is used to set the maximum number of iterations.
[0030] In this embodiment of the application, the specific components are: input channel matrix H, matrix dimension N, truncation factor a, and received signal Data.
[0031] The initial iteration count is set. It also sets a maximum number of iterations N.
[0032] S120: Perform singular value decomposition on the channel matrix, and discard singular values and corresponding eigenvectors that are less than a preset condition according to the truncation factor to obtain the reconstructed channel matrix.
[0033] In this embodiment of the application, singular value decomposition is performed on the channel matrix H. ,in, For the channel matrix, It is a left singular matrix. It is a singular value diagonal matrix. It is a right singular matrix.
[0034] It should be noted that U is a unitary matrix whose column vectors are the left singular vectors of H; S is a diagonal matrix where the diagonal elements are non-negative and arranged in descending order, and these elements are called the singular values of H; V is a unitary matrix whose column vectors are the right singular vectors of H.
[0035] When the following conditions are met:
[0036] Set the k-th eigenvalue and its corresponding eigenvector to zero and reconstruct the channel matrix. ,in, The truncated left singular matrix, This is the truncated singular value diagonal matrix. This is the truncated right singular matrix. This indicates truncated singular value decomposition (TSVD).
[0037] S130: Calculate the pseudo-inverse of the reconstructed channel matrix and obtain the estimated value of the current path signal through zero-forcing detection.
[0038] In this embodiment of the application, the pseudo-inverse of the reconstructed channel matrix is calculated. The estimated value of the nth signal is obtained by performing zero-forcing detection on the nth signal. ,in, Let be the estimated value of the nth signal, and A be the pseudo-inverse of the reconstructed channel matrix. This is the nth row of the pseudo-inverse A, where Data is the current received signal.
[0039] S140: After quantizing and deciding the estimated value, eliminate the current path interference from the received signal and update the received signal.
[0040] In this embodiment of the application, the estimated value of the signal is used. After quantization and decision-making, the signal from the receiving end is then... The receiver signal is updated by subtracting this signal from the input. .
[0041] S150: Set the corresponding column in the channel matrix to zero, proceed to the next signal detection, and repeat steps S110 to S140 until the maximum number of iterations is reached and the detection result is output.
[0042] In this embodiment of the application, the corresponding matrix column vector is set to zero. Proceed to steps S110-S140, treat the above process as one iteration and increment the iteration count by 1. Continue until the preset maximum number of iterations is reached. At this point, the final detection result will be output.
[0043] In some implementations, see Figure 3 The diagram shows a model structure of an exemplary LOSMIMO system.
[0044] Figure 3 The model includes QPSK modulation, receiver preamplifier, MIMO detector, and QPSK demodulation.
[0045] In this context, dt represents the spacing between the transmitting antenna elements and dr represents the spacing between the receiving antenna elements. After QPSK modulation, the signal is mapped to the antenna for transmission and then received. The received signal is input to the transmitter at the receiving end for simulated attenuation. The resulting signal is then input to the MIMO detector.
[0046] Figure 3 In a hybrid MIMO detection method, the preprocessing steps include: S210 to S230, wherein: S210: Performs QPSK modulation on each input signal and maps it onto the transmitting antenna for transmission; S220: The signal from the transmitting end propagates to the receiving end via a line-of-sight channel. The receiving end simulates channel fading through a signal amplifier and performs signal detection using the method described in claim 1. S230: Demodulates the detected signal and outputs an estimated signal value.
[0047] For example, the quantization decision in this application is a demodulation decision based on QPSK modulation; the implementation steps are described in [reference needed]. Figure 2 The hybrid MIMO detection method shown combines a zero-forcing detection algorithm with a truncated singular value algorithm with an interference cancellation algorithm. Its steps include: S1: Input channel matrix H, truncation factor a, eigenvector V.
[0048]
[0049] in, This represents the channel gain from the j-th transmit antenna to the i-th receive antenna. The cutoff factor is set to a = 2e4. Received signal. .
[0050] S2: .
[0051] The initial iteration count n=1 is set, and the maximum iteration count N is set, where N represents the matrix dimension.
[0052] S3: Calculate the pseudoinverse A of the truncated matrix, the right eigenvector matrix Vt of the truncated matrix, and the number of non-zero singular values k after truncation. ); First, perform singular value decomposition on the channel matrix H. ; Specifically: When the maximum singular value With the kth singular value When the ratio is greater than or equal to a, retain the element and its corresponding left and right eigenvectors; when the maximum singular value... With the kth singular value When the ratio is less than a, the element and its corresponding left and right eigenvectors are set to 0, i.e.
[0053] Reconstruct the channel matrix
[0054] Find the pseudo-inverse matrix A of the reconstructed channel matrix. , express The transpose of .
[0055] S4: Calculate the coefficient matrix In the formula, This represents a k-1 row, m column identity matrix. The truncated right eigenvector matrix. V represents the original right eigenvector matrix.
[0056] S5: Calculate the proportion of the diagonal elements in each row of the coefficient matrix within that row.
[0057] In the formula, This represents the element in the nth row and nth column of the coefficient matrix. This represents the absolute value of the element in the nth row and 1st column of the coefficient matrix. This represents the absolute value of the element in the nth row and second column of the coefficient matrix. This represents the absolute value of the element in the nth row and 3rd column of the coefficient matrix. This represents the absolute value of the element in the nth row and 4th column of the coefficient matrix.
[0058] S5: Calculate the signal with the largest Q value. .
[0059] S6: Calculate the nth signal .
[0060] S7: After quantizing and deciding the estimated value of the nth signal, subtract the signal from the received signal.
[0061] S8: Set the corresponding matrix column vectors to zero. .
[0062] In summary, the hybrid MIMO detection method provided in this application, when propagating in a line-of-sight channel and the jammer and target are close to each other, effectively recovers the signal and reduces the bit error rate, unlike traditional linear detection algorithms such as zero-forcing detection, serial interference cancellation, and minimum mean square error algorithm, which are all ineffective in such cases.
[0063] Please see Figure 4 , Figure 4 This is a structural block diagram of a hybrid MIMO detection device provided by the present invention. The device includes: an acquisition module 310, a reconstruction module 320, a detection module 330, an update module 340, and an output module 350, wherein: The acquisition module 310 is used to acquire the channel matrix, matrix dimension, truncation factor and received signal, wherein the matrix dimension is used to set the maximum number of iterations; The reconstruction module 320 is used to perform singular value decomposition on the channel matrix and discard singular values and corresponding eigenvectors that are less than a preset condition according to the truncation factor to obtain the reconstructed channel matrix. The detection module 330 is used to obtain the pseudo-inverse of the reconstructed channel matrix and obtain the estimated value of the current path signal through zero-forcing detection; The update module 340 is used to quantize and decide the estimated value, eliminate the current path interference from the received signal, and update the received signal. The output module 350 is used to set the corresponding column in the channel matrix to zero, proceed to the next signal detection, and repeat steps S110 to S140 until the number of iterations reaches the maximum number of iterations and output the detection result.
[0064] It should be noted that the device embodiments in this invention correspond to the aforementioned method embodiments. The specific principles in the device embodiments can be found in the content of the aforementioned method embodiments, and will not be repeated here.
[0065] In the several embodiments provided in this example, the coupling between modules can be electrical, mechanical, or other forms of coupling.
[0066] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module. The integrated modules described above can be implemented in hardware or as software functional modules.
[0067] Please see Figure 5 , Figure 5 This is a structural block diagram of an electronic device 200 that can perform the above-described hybrid MIMO detection method, provided as an embodiment of this application. The electronic device 200 may be a smartphone, tablet computer, computer, or portable computer.
[0068] The electronic device 200 also includes a processor 202 and a memory 204. The memory 204 stores programs that can execute the contents of the foregoing embodiments, and the processor 202 can execute the programs stored in the memory 204.
[0069] The processor 202 may include one or more cores for data processing and message matrix units. The processor 202 connects to various parts of the electronic device 200 using various interfaces and lines, and performs various functions and processes data by running or executing instructions, programs, code sets, or instruction sets stored in the memory 204, and by calling data stored in the memory 204. Optionally, the processor 202 may be implemented using at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). The processor 202 may integrate one or more of the following: Central Processing Unit (CPU), Graphics Processing Unit (GPU), and modem / decoder. The CPU primarily handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the displayed content; and the modem is used for wireless communication. It is understood that the modem / decoder may also not be integrated into the processor and may be implemented separately through a communication chip.
[0070] Memory 204 may include random access memory (RAM) or read-only memory (ROM). Memory 204 can be used to store instructions, programs, code, code sets, or instruction sets. Memory 204 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for implementing at least one function (e.g., instructions for a user to obtain random numbers), instructions for implementing the various method embodiments described below, etc. The data storage area may also store data (e.g., random numbers) created by the terminal during use.
[0071] Electronic device 200 may also include a network module and a screen. The network module is used to receive and transmit electromagnetic waves, converting electromagnetic waves into electrical signals, thereby enabling communication with communication networks or other devices, such as audio playback devices. The network module may include various existing circuit elements used to perform these functions, such as antennas, radio frequency transceivers, digital signal processors, encryption / decryption chips, SIM cards, memory, etc. The network module can communicate with various networks such as the Internet, corporate intranets, and wireless networks, or communicate with other devices via wireless networks. The aforementioned wireless networks may include cellular telephone networks, wireless local area networks, or metropolitan area networks. The screen can display interface content and facilitate data interaction.
[0072] Please refer to Figure 6 , Figure 6 This diagram illustrates a structural block diagram of a computer-readable storage medium according to an embodiment of this application. The computer-readable storage medium 400 stores program code 410, which can be called by a processor to execute the methods described in the above method embodiments.
[0073] The computer-readable storage medium 400 may be an electronic memory such as flash memory, EEPROM (Electrically Erasable Programmable Read-Only Memory), EPROM, hard disk, or ROM. Optionally, the computer-readable storage medium includes a non-transitory computer-readable storage medium. The computer-readable storage medium 400 has storage space for program code 410 that performs any of the method steps described above. This program code 410 can be read from or written to one or more computer program products. The program code 410 may be compressed, for example, in a suitable form.
[0074] This application also provides a computer program product or computer program that includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform a hybrid MIMO detection method described in the various optional implementations above.
[0075] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims
1. A hybrid MIMO detection method, characterized in that, The method includes: S110: Obtain the channel matrix, matrix dimension, truncation factor, and received signal, wherein the matrix dimension is used to set the maximum number of iterations; S120: Perform singular value decomposition on the channel matrix, and discard singular values and corresponding eigenvectors that are less than a preset condition according to the truncation factor to obtain the reconstructed channel matrix; S130: Calculate the pseudo-inverse of the reconstructed channel matrix and obtain the estimated value of the current path signal through zero-forcing detection; S140: After quantizing and deciding the estimated value, eliminate the current path interference from the received signal and update the received signal; S150: Set the corresponding column in the channel matrix to zero, proceed to the next signal detection, and repeat steps S110 to S140 until the maximum number of iterations is reached and the detection result is output.
2. The hybrid MIMO detection method according to claim 1, characterized in that, Expressions that discard singular values based on preconditions include: In the formula, For the maximum singular value, For the first A singular value, This is the cutoff factor.
3. The hybrid MIMO detection method according to claim 1, characterized in that, The expression for performing singular value decomposition on the channel matrix includes: In the formula, For the channel matrix, It is a left singular matrix. It is a singular value diagonal matrix. It is a right singular matrix.
4. The hybrid MIMO detection method according to claim 1, characterized in that, The process of obtaining the estimated value of the current path signal through zero-forcing detection includes: The estimated value of the current path signal is obtained using the first calculation formula, which is: In the formula, Let be the estimated value of the nth signal, and A be the pseudo-inverse of the reconstructed channel matrix. This is the nth row of the pseudo-inverse A, where Data is the current received signal.
5. The hybrid MIMO detection method according to claim 1, characterized in that, The quantization decision is a demodulation decision based on QPSK modulation.
6. The hybrid MIMO detection method according to claim 5, characterized in that, The hybrid MIMO detection method further includes a preprocessing step, specifically: The input signals are QPSK modulated and mapped onto the transmitting antenna for transmission. The transmitting signal propagates to the receiving end via a line-of-sight channel. The receiving end simulates channel fading through a signal amplifier and performs signal detection using the method described in claim 1. The detected signal is demodulated, and the estimated signal value is output.
7. The hybrid MIMO detection method according to claim 1, characterized in that, The hybrid MIMO detection method further includes: reconstructing the channel matrix, the expression of which is: In the formula, The truncated left singular matrix, This is the truncated singular value diagonal matrix. This is the truncated right singular matrix. This indicates a truncated singular value decomposition.
8. A hybrid MIMO detection device, characterized in that, The device includes: The acquisition module is used to acquire the channel matrix, matrix dimension, truncation factor, and received signal, wherein the matrix dimension is used to set the maximum number of iterations; The reconstruction module is used to perform singular value decomposition on the channel matrix and discard singular values and corresponding eigenvectors that are less than a preset condition according to the truncation factor to obtain the reconstructed channel matrix. The detection module is used to obtain the pseudo-inverse of the reconstructed channel matrix and to obtain the estimated value of the current path signal through zero-forcing detection. The update module is used to quantize and decide the estimated value, eliminate the current path interference from the received signal, and update the received signal. The output module is used to set the corresponding column in the channel matrix to zero, proceed to the next signal detection, and repeat steps S110 to S140 until the number of iterations reaches the maximum number of iterations and output the detection result.
9. An electronic device, characterized in that, The electronic device includes a memory and a processor. The memory stores program code that can run on the processor. When the program code is executed by the processor, it implements a hybrid MIMO detection method as described in any one of claims 1-7.
10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores program code that can be called by one or more processors to execute a hybrid MIMO detection method as described in any one of claims 1-7.