High-dimensional MIMO-OFDM implementation method and system based on space diversity

Abstract

The invention belongs to the field of wireless communication, and particularly discloses a high-dimensional MIMO-OFDM (Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing) implementation method and system based on space diversity. At a sending end, an input binary sequence is subjected to symbol mapping through a high-dimensional signal constellation diagram, space-time coding is carried out on a mapped high-dimensional signal coordinate component, fast Fourier inversion is carried out on each space-time code word, signals are converted from a frequency domain to a time domain, cyclic prefixes are added, and a high-dimensional signal is obtained. Signals are transmitted to a wireless channel through different antennas. At a receiving end, the time domain signal of each receiving antenna is subjected to cyclic prefix removal, then Fourier transform is carried out, the time domain signal is converted into a frequency domain signal, and an MIMO detector adopts a maximum likelihood or minimum mean square error algorithm, and after space-time decoding and high-dimensional signal de-mapping are carried out, an originally sent binary sequence is recovered. According to the invention, the spectrum efficiency can be improved and the system reliability can be enhanced.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of wireless communication, and more particularly, relates to a high-dimensional MIMO-OFDM implementation method and system based on spatial diversity. BACKGROUND

[0002] Orthogonal frequency division multiplexing (OFDM) technology is a core physical layer modulation technology in modern mobile communication, especially in the field of 4G and 5G mobile communication, and also plays an important role in today's research and development towards 6G. Compared with traditional single-carrier digital signal transmission technology, OFDM is a multi-carrier modulation scheme, which has the advantages of high spectrum efficiency, effective anti-multipath interference and anti-frequency selective fading. In traditional OFDM systems, digital baseband signal modulation generally uses two-dimensional signal constellation diagrams such as multi-phase shift keying (MPSK) and multi-quadrature amplitude modulation (MQAM), and the signal points are distributed in a two-dimensional plane. However, such a system based on a two-dimensional signal constellation diagram has limitations in reliability, and the minimum Euclidean distance between the signal points is relatively small, which limits the performance of the system in a noisy environment.

[0003] Therefore, how to effectively improve the system reliability is a problem that needs to be solved at present. SUMMARY

[0004] In view of the defects of the prior art, the purpose of the present application is to provide a high-dimensional MIMO-OFDM implementation method and system based on spatial diversity, which can ensure the reliability of the system.

[0005] To achieve the above-mentioned purpose, in a first aspect, the present application provides a high-dimensional MIMO-OFDM implementation method based on spatial diversity, comprising the following steps: S10, grouping a serial bit stream to be transmitted into parallel groups of k bits each, where k=log2M, M is the size of a high-dimensional signal constellation diagram, and mapping the k bits of each parallel group to a D-dimensional high-dimensional symbol, where D≥3; S20, space-time encoding a plurality of the high-dimensional symbols to generate a space-time code array; S30, performing inverse fast Fourier transform on each row vector of the space-time code array to obtain a time-domain signal, and adding a cyclic prefix to the time-domain signal, and transmitting through N T antennas, where N T =D; S40, receiving the time-domain signal through N R antennas, removing the cyclic prefix from the received signal, and performing fast Fourier transform on the signal after removing the cyclic prefix to obtain a frequency-domain signal, where N R ≥N T ; S50, perform MIMO detection on the frequency domain signal to obtain an estimate of the transmitted signal, perform space-time decoding on the estimate to recover the high-dimensional symbol, demap the high-dimensional symbol to recover k parallel information bits, and finally convert the k parallel information bits into a serial binary sequence to recover the original transmitted bit stream.

[0006] The high-dimensional MIMO-OFDM implementation method based on spatial diversity provided in this application has the following effects: By mapping the serial bit stream to a high-dimensional signal constellation diagram with a dimension of at least three, the noise margin of the system can be directly improved by utilizing the larger minimum Euclidean distance of the high-dimensional constellation diagram compared to the traditional two-dimensional constellation diagram; by performing space-time coding on the high-dimensional symbols and transmitting them using multiple antennas, each coordinate component of the high-dimensional signal can undergo independent channel fading, thereby obtaining spatial diversity gain and enhancing the system's robustness against multipath fading; at the receiving end, through multi-antenna reception and MIMO detection, the signal components transmitted on different antennas can be effectively separated and recovered, and by combining space-time decoding and high-dimensional signal demapping, the original transmitted information can be accurately restored. This method combines the inherent shaping gain of high-dimensional signals with the spatial diversity gain of multi-antenna systems, and significantly improves the transmission reliability of communication systems in fading channel environments without relying on additional bandwidth through the coordinated processing of signal and spatial dimensions.

[0007] As a further preferred embodiment, in step S20, the space-time coding includes: performing space-time coding for every N high-dimensional symbols as a group to generate a space-time code array X. ST , where X ST It is a matrix with D rows and N columns. The element in the d-th row and n-th column of the matrix is ​​the d-th dimension coordinate component of the n-th high-dimensional symbol, where 0≤d≤D-1, 0≤n≤N-1, and N is the number of OFDM subcarriers.

[0008] As a further preferred embodiment, in step S50, the space-time decoding includes: for each estimated value X' (n) Perform space-time decoding, decoding into a high-dimensional symbol S' D .

[0009] As a further preferred embodiment, in step S20, the space-time coding includes: performing space-time coding for every 2N high-dimensional symbols as a group, combining the corresponding dimensional coordinate components of every two adjacent high-dimensional symbols into a complex number to generate a space-time code array X. ST , where X ST It is a matrix with D rows and N columns. The element in the d-th row and n-th column of the matrix is ​​the d-th dimension coordinate component of the 2n-th high-dimensional symbol plus the d-th dimension coordinate component of the 2n+1-th high-dimensional symbol multiplied by the imaginary unit j, where 0≤d≤D-1, 0≤n≤N-1, N is the number of OFDM subcarriers, and j represents the imaginary number.

[0010] As a further preferred embodiment, in step S50, the space-time decoding includes: converting each estimated value X' (n) The code is decoded into two high-dimensional symbols S' D That is, by X' (n) All real parts form a column vector, which is decoded into a high-dimensional symbol, represented by X'. (n) All the imaginary parts form a column vector, which is decoded into another high-dimensional symbol.

[0011] As a further preferred embodiment, in step S10, the high-dimensional signal constellation diagram is represented as a two-dimensional matrix S. D The structure has dimensions of D rows and M columns, where the m-th D-dimensional symbol is represented as a column vector S. D (m) = [W0(m) W1(m) … W d (m)... W D-1 (m)] T T represents the transpose operation, W d Let d represent the d-th real coordinate component of the high-dimensional symbol, 0≤d≤D-1, 0≤m≤M-1.

[0012] As a further preferred embodiment, in step S30, the length of the cyclic prefix is ​​greater than the maximum multipath delay of the wireless channel.

[0013] As a further preferred option, in step S50, the MIMO detection employs either the maximum likelihood detection algorithm or the minimum mean square error detection algorithm.

[0014] As a further preferred embodiment, the high-dimensional signal constellation diagram is a D-dimensional M-ary signal constellation diagram, where D≥3 and M≥4.

[0015] Secondly, this application provides a high-dimensional MIMO-OFDM system based on spatial diversity for implementing any of the methods described above, including a transmitter and a receiver; The sending end includes: The serial-to-parallel conversion module is used to group the serial bit stream to be transmitted into parallel groups of k bits each, where k = log2M and M is the size of the high-dimensional signal constellation diagram. A high-dimensional signal mapper module is used to map k bits of each parallel group to a D-dimensional high-dimensional symbol, where D≥3; A high-dimensional signal space-time encoder module is used to perform space-time encoding on the high-dimensional symbols to generate a space-time code array; The N-point inverse fast Fourier transform module is used to perform inverse fast Fourier transform on each row vector of the space-time code array, converting the frequency domain signal into a time domain signal. The cyclic prefix module is used to add a cyclic prefix to the time-domain signal, and through N TN antennas transmit, where N T =D; The receiving end includes: The module for removing cyclic prefixes is used to process N. R The time-domain signal received by each receiving antenna is stripped of its cyclic prefix, where N R ≥N T ; The N-point Fast Fourier Transform module is used to perform Fast Fourier Transform on the time-domain signal after removing the cyclic prefix, converting the time-domain signal into a frequency-domain signal. The MIMO detector module is used to detect the frequency domain signal and obtain an estimate of the transmitted signal. A high-dimensional signal space-time decoder module is used to perform space-time decoding on the estimated value to recover the high-dimensional symbol; A high-dimensional signal demapping module is used to demap the high-dimensional symbol back to k parallel information bits; The parallel-to-serial conversion module is used to convert the k parallel information bits into a serial binary sequence to recover the original transmitted bit stream.

[0016] It is understandable that the beneficial effects of the second aspect mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here. Attached Figure Description

[0017] Figure 1 This is a flowchart of the high-dimensional MIMO-OFDM implementation method based on spatial diversity provided in this application; Figure 2 This is a structural block diagram of the transmitter in a high-dimensional MIMO-OFDM system based on spatial diversity provided in the embodiments of this application; Figure 3 This is a block diagram of the receiver in a high-dimensional MIMO-OFDM system based on spatial diversity provided in the embodiments of this application; Figure 4 This is a comparison chart of simulation results provided in the embodiments of this application. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0019] This application's research reveals that digital signals can be distributed in higher-dimensional spaces, such as three-dimensional or four-dimensional signal constellation diagrams. Under the same constellation diagram size and average power, higher-dimensional signal constellation diagrams have a larger minimum Euclidean distance than traditional two-dimensional signals, and the greater noise margin they provide can directly and effectively improve the reliability of digital communication systems. However, while current research on three-dimensional OFDM systems can effectively improve the reliability of traditional OFDM systems based on two-dimensional signal constellation diagrams, the bandwidth utilization (spectral efficiency) of these systems is relatively low.

[0020] Furthermore, compared to traditional Single-Input Single-Output (SISO) technology, Multiple-Input Multiple-Output (MIMO) technology can significantly improve channel capacity. This technology can generate independent parallel channels in space to transmit multiple data streams simultaneously, increasing spectral efficiency without increasing system bandwidth, and effectively improving the transmission rate of wireless communication systems. 4G utilizes MIMO technology to improve the system performance of wireless communication. The massive MIMO technology proposed in 5G, with tens or even hundreds of times more receiving antennas than 4G, greatly increases the communication efficiency of 5G and is also an essential technology for 6G. Although single-carrier MIMO technology can improve bandwidth utilization and system performance, its system performance is poor in fading channel environments. This application leverages the advantages of OFDM technology, combining MIMO and OFDM technologies to achieve both high data transmission rates and strong system reliability through diversity. MIMO-OFDM technology is a new technology that combines MIMO and OFDM technologies. It utilizes time, frequency and space diversity techniques to significantly enhance the tolerance of wireless communication systems to noise, interference and multipath. The combination of the two has great advantages in improving the effectiveness and reliability of wireless communication.

[0021] like Figure 1 As shown, this application provides a high-dimensional MIMO-OFDM implementation method based on spatial diversity, including steps S10 to S50, which are detailed below: Step S10: Divide the serial bit stream to be sent into parallel groups of k bits each, where k = log2M, M is the size of the high-dimensional signal constellation diagram, and map the k bits of each parallel group to a D-dimensional high-dimensional symbol, where D ≥ 3.

[0022] This step involves symbol mapping using a high-dimensional signal constellation diagram. The larger minimum Euclidean distance of the high-dimensional signal constellation diagram compared to the traditional two-dimensional signal constellation diagram provides greater noise margin, thereby improving the reliability of the digital communication system.

[0023] Step S20: Perform space-time encoding on multiple high-dimensional symbols to generate a space-time code array.

[0024] This step extends the coordinate components of high-dimensional symbols to the spatial dimension through space-time coding. By utilizing the spatial diversity gain of MIMO technology, different coordinate components of high-dimensional signals can be transmitted through different antennas, thereby enhancing the system's ability to resist channel fading.

[0025] Step S30: Perform an inverse fast Fourier transform on each row vector of the space-time code array to obtain the time-domain signal, and add a cyclic prefix to the time-domain signal, using N... T N antennas transmit, where N T =D.

[0026] This step converts the frequency domain signal to the time domain using inverse fast Fourier transform and adds a cyclic prefix, which can effectively resist multipath interference and frequency selective fading. At the same time, it transmits signals through multiple antennas and uses spatial diversity to improve transmission reliability.

[0027] Step S40, via N R Each antenna receives a time-domain signal. The received signal is then de-cyclic-prefixed, and a Fast Fourier Transform is performed on the de-cyclic-prefixed signal to obtain the frequency-domain signal, where N... R ≥N T .

[0028] This step processes the received signal by removing the cyclic prefix and performing a fast Fourier transform, which can recover the frequency domain signal and prepare it for subsequent MIMO detection. It also utilizes multiple receiving antennas to enhance the diversity of signal reception.

[0029] Step S50: Perform MIMO detection on the frequency domain signal to obtain an estimate of the transmitted signal, perform space-time decoding on the estimate to recover the high-dimensional symbol, demap the high-dimensional symbol into k parallel information bits, and finally convert the k parallel information bits into a serial binary sequence to recover the original transmitted bit stream.

[0030] This step uses MIMO detection and space-time decoding to process the received signal, which can accurately estimate the transmitted high-dimensional symbols and recover the original bit stream by demapping the high-dimensional signal, thus achieving reliable signal reception.

[0031] The high-dimensional MIMO-OFDM implementation method based on spatial diversity provided in this application has the following effects: By mapping the serial bit stream to a high-dimensional signal constellation diagram with a dimension of at least three, the noise margin of the system can be directly improved by utilizing the larger minimum Euclidean distance of the high-dimensional constellation diagram compared to the traditional two-dimensional constellation diagram; by performing space-time coding on the high-dimensional symbols and transmitting them using multiple antennas, each coordinate component of the high-dimensional signal can undergo independent channel fading, thereby obtaining spatial diversity gain and enhancing the system's robustness against multipath fading; at the receiving end, through multi-antenna reception and MIMO detection, the signal components transmitted on different antennas can be effectively separated and recovered, and by combining space-time decoding and high-dimensional signal demapping, the original transmitted information can be accurately restored. This method combines the inherent shaping gain of high-dimensional signals with the spatial diversity gain of multi-antenna systems, and significantly improves the transmission reliability of communication systems in fading channel environments without relying on additional bandwidth through the coordinated processing of signal and spatial dimensions.

[0032] In one embodiment, the technical solution to achieve the above objective can be as follows: In order to improve the bandwidth utilization and reliability of OFDM systems based on high-dimensional signals, this embodiment provides a method and system for implementing high-dimensional MIMO-OFDM based on spatial diversity technology.

[0033] like Figure 2 As shown, the transmitter of the high-dimensional MIMO-OFDM system based on spatial diversity provided in this embodiment includes: a serial-to-parallel conversion module, a high-dimensional signal mapper module, a high-dimensional signal space-time encoder module, an N-point inverse fast Fourier transform (IFFT) module, and a cyclic prefix addition module.

[0034] like Figure 3 As shown, the receiver of the high-dimensional MIMO-OFDM system based on spatial diversity provided in this embodiment includes: a cyclic prefix removal module, an N-point fast Fourier transform (FFT) module, a MIMO detector module, a high-dimensional signal space-time decoder module, a high-dimensional signal demapping module, and a parallel-to-serial conversion module.

[0035] The spatial diversity-based high-dimensional MIMO-OFDM system in this embodiment includes the following steps: S1: Input the serial bit stream to be transmitted into the serial-to-parallel conversion module. The serial-to-parallel conversion module groups the input bit stream, that is, each k = log2M bit is grouped in parallel. M represents the modulation order of the digital modulation system or the size of the high-dimensional signal constellation diagram used. Then, the k-bit binary sequence is converted into decimal data m, 0 ≤ m ≤ M-1, which is used as the constellation diagram symbol index and input to the high-dimensional signal mapper module.

[0036] For example, when M=8, for the input binary sequence, the serial-to-parallel transformation operation is performed in groups of 3 bits, i.e., k = log28 = 3.

[0037] S2: The high-dimensional signal mapper maps high-dimensional symbols based on the input symbol index information. A D-dimensional signal constellation diagram of size M can be represented as a two-dimensional matrix S. D ,Right now

[0038] The m-th D-dimensional symbol in a high-dimensional signal constellation diagram can be represented as a one-dimensional column vector S. D (m) = [W0(m)W1(m) … W d (m)... W D-1 (m)] T T represents the transpose operation, W d Let d represent the d-th real coordinate component of the high-dimensional symbol, where 0 ≤ d ≤ D-1 and D ≥ 3. Based on the input high-dimensional symbol index, the high-dimensional signal mapper outputs a D-dimensional column vector for each k bits.

[0039] For example, when D=3 and M=4, a three-dimensional quaternary high-dimensional signal constellation diagram can be represented as:

[0040] S3: The high-dimensional signal space-time encoder module performs space-time encoding based on the input high-dimensional symbol coordinate values. This embodiment provides two methods to achieve spatial diversity of high-dimensional symbols.

[0041] S31: Method 1, for the high-dimensional symbol column vector output in step S2, each coordinate component of the high-dimensional symbol is transmitted through a different antenna, i.e., the number of transmitting antennas N. T =D, then perform space-time encoding on groups of N high-dimensional symbols, resulting in a space-time code array X. ST Represented as:

[0042] S D (n) ∈S D , 0 ≤ n ≤ N-1, represents X ST The nth high-dimensional symbol in the method is sent by each space-time code array of method one.

[0043] For example, when D = 3 and N = 4, the encoded space-time code array X ST Represented as:

[0044] S32: Method 2, unlike Method 1 which sends N high-dimensional symbols per space-time code array, in order to improve spectral efficiency, Method 2 combines every two adjacent high-dimensional symbols into a complex data number. Each space-time code array sends 2N high-dimensional symbols. The recombined and encoded space-time code array is represented as follows:

[0045] That is, the corresponding dimensional coordinate components of each two adjacent high-dimensional symbols form a complex number data, where j represents an imaginary number.

[0046] For example, when D = 3 and N = 4, the encoded space-time code array X ST Represented as:

[0047] S4: The space-time code array X generated in step S3 ST Each row vector X d , 0≤d≤D-1(=N) T -1) The inverse fast Fourier transform (IFFT) operation is performed through the N-point IFFT module to convert the frequency domain OFDM signal generated in step S3 to the time domain, resulting in the time domain signal x. ST It can be represented as:

[0048] The ifft(·) function represents the inverse fast Fourier transform operation.

[0049] S5: In the module that adds the loop prefix, for x ST Each time-domain OFDM signal x d Add a cyclic prefix, the length of which is greater than the maximum multipath delay of the wireless channel, to reduce inter-symbol interference (ISI). Then, use N... T =D antennas transmit D OFDM signals to the channel.

[0050] S6: In each decyclic prefix module at the receiver, for N R The received time-domain signal on the root receiving antenna undergoes cyclic prefix removal processing. In this embodiment, N is set to N. R ≥N T .

[0051] S7: For the output signal of each decyclic prefix module, perform a Fast Fourier Transform (FFT) operation in each N-point FFT module to transform the received time-domain signal y. ST = [y (0) y (1) …y (N-1) Transform to the frequency domain, where y (n) Represents matrix y STThe nth column of the signal, the converted frequency domain signal Y ST It can be represented as:

[0052] Where y r 0 ≤ r ≤ N R -1 represents the time-domain OFDM signal on the r-th receiving antenna, i.e., y ST The N-dimensional row vector Y in the r-th row of the vector. r This represents the frequency-domain OFDM signal recovered from each receiving antenna. The fft(·) function represents the Fast Fourier Transform operation. The received frequency-domain OFDM signal matrix is ​​represented as Y. ST =HX ST +N AWGN H represents the channel matrix, which is an N R ×N T A two-dimensional matrix, N AWGN This represents additive white Gaussian noise (AWGN), which is an N... R 3D column vector, X ST = [X (0) X (1) …X (N – 1) ] NT×N This represents the matrix of transmitted OFDM signals in the frequency domain.

[0053] S8: In the MIMO detector module, the received signal Y... ST Each column vector Y in (n) Perform maximum likelihood (ML) detection or minimum mean square error (MMSE) detection to obtain an estimate of the transmitted signal X'. (n) ,Right now

[0054] S9: In the high-dimensional signal space-time decoder module, for the space-time coding scheme of method one in S31, each X' (n) Decoded into a high-dimensional symbol S' D For the space-time coding scheme of S32 method two, each X' (n) The code is decoded into two high-dimensional symbols S' D That is, by X' (n) All real parts form a column vector, which is decoded into a high-dimensional symbol, represented by X'. (n) All the imaginary parts form a column vector, which is decoded into another high-dimensional symbol.

[0055] S10: In the high-dimensional signal demapping module, each received high-dimensional symbol S' D The high-dimensional signal is demapped to recover k parallel information bits.

[0056] S11: The parallel-to-serial conversion module performs the opposite operation to step S1, converting k parallel information bits into a serial binary sequence to restore the original transmitted bit stream.

[0057] The beneficial effects of the technical solution provided in this embodiment: (1) The space-time coding and decoding algorithm is simple. This embodiment provides two space-time coding schemes: Method 1 directly extends each real coordinate component of the high-dimensional signal to the spatial dimension, and each coordinate component is transmitted through an antenna; Method 2, in order to improve the bandwidth utilization of the system, merges two high-dimensional symbols into a complex signal with the same dimension as the signal, and then transmits it through different antennas. Both space-time coding methods are easy to implement in hardware circuits.

[0058] (2) Significantly improved spectral efficiency. In traditional three-dimensional OFDM systems, each symbol transmits only one coordinate component of the three-dimensional signal. Compared with traditional two-dimensional OFDM systems, although the system reliability is improved, the spectral efficiency is only one-third that of the two-dimensional system. This embodiment utilizes two space-time coding schemes, Method 1 and Method 2, and employs MIMO technology. Under the same channel bandwidth conditions, the spectral efficiency of Method 1 is the same as that of the two-dimensional OFDM system, while the spectral efficiency of Method 2 is twice that of the two-dimensional OFDM system, achieving a significant improvement in spectral efficiency.

[0059] (3) Better system reliability. On the one hand, the high-dimensional signal constellation diagram provides a larger minimum Euclidean distance than the corresponding two-dimensional signal constellation diagram, with a larger noise margin and better system performance; on the other hand, by utilizing the spatial diversity of MIMO technology, the coordinate components of the high-dimensional signal are transmitted through different antennas, and the high diversity gain makes the system more reliable.

[0060] The following is a specific implementation example of this application: This specific embodiment provides a high-dimensional MIMO-OFDM system based on spatial diversity. It assumes the use of a three-dimensional octal signal constellation diagram, i.e., M=8, D=3, with the coordinates of all symbols shown in Table 1. Other parameters are as follows: the number of antennas used, N... T =N R =3, OFDM signal subcarrier number N = 128, cyclic prefix length is 16, transmission environment is frequency-selective Rayleigh multipath fading channel, and the number of paths in the multipath channel is 10. The transmitter sends 10 6 Frame OFDM signal, used for bit error rate statistics at the receiver.

[0061] Table 1

[0062] When using Method 1 of this embodiment for space-time coding, the simulation results are as follows: Figure 4 As shown, in order to compare the system performance of this embodiment, Figure 4 Simulation results for a traditional SISO-OFDM system based on 8QAM are also provided. The two systems have the same channel environment and spectral efficiency. Figure 2 The simulation results show that the system in this embodiment has better system reliability, and the performance gain comes from the shaping gain of the high-dimensional signal constellation diagram and the diversity gain of MIMO technology.

[0063] The key technical point of this embodiment is: (1) Space-time coding algorithm for high-dimensional signals. This embodiment provides two space-time coding schemes for high-dimensional signals: Method 1 directly extends each real coordinate component of the high-dimensional signal to the spatial dimension, and each coordinate component is transmitted through an antenna; Method 2, in order to improve the bandwidth utilization of the system, merges two high-dimensional symbols into a complex signal with the same signal dimension, and then transmits it through different antennas.

[0064] (2) This embodiment provides a MIMO-OFDM based on high-dimensional signal constellation mapping, which improves the traditional three-dimensional signal SISO transmission scheme to a higher spatial dimension through space-time coding, uses multiple antennas to transmit high-dimensional signals, makes full use of the spatial diversity gain of MIMO technology, and effectively improves the spectral efficiency and reliability of traditional three-dimensional OFDM systems.

[0065] Those skilled in the art will readily understand that the above description is merely a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for implementing high-dimensional MIMO-OFDM based on spatial diversity, characterized in that, Includes the following steps: S10, divide the serial bit stream to be sent into parallel groups of k bits each, where k = log2M, M is the size of the high-dimensional signal constellation diagram, and map the k bits of each parallel group to a D-dimensional high-dimensional symbol, where D ≥ 3; S20, perform space-time encoding on the multiple high-dimensional symbols to generate a space-time code array; S30, perform a fast inverse Fourier transform on each row vector of the space-time code array to obtain a time-domain signal, and add a cyclic prefix to the time-domain signal, through N T N antennas transmit, where N T =D; S40, via N R Each antenna receives a time-domain signal. The received signal is then de-cyclic-prefixed, and a Fast Fourier Transform is performed on the de-cyclic-prefixed signal to obtain the frequency-domain signal, where N... R ≥N T ; S50, perform MIMO detection on the frequency domain signal to obtain an estimate of the transmitted signal, perform space-time decoding on the estimate to recover the high-dimensional symbol, demap the high-dimensional symbol to recover k parallel information bits, and finally convert the k parallel information bits into a serial binary sequence to recover the original transmitted bit stream.

2. The high-dimensional MIMO-OFDM implementation method based on spatial diversity as described in claim 1, characterized in that, In step S20, the space-time coding includes: performing space-time coding for every N high-dimensional symbols as a group to generate a space-time code array X. ST , where X ST It is a matrix with D rows and N columns. The element in the d-th row and n-th column of the matrix is ​​the d-th dimension coordinate component of the n-th high-dimensional symbol, where 0≤d≤D-1, 0≤n≤N-1, and N is the number of OFDM subcarriers.

3. The high-dimensional MIMO-OFDM implementation method based on spatial diversity as described in claim 2, characterized in that, In step S50, the space-time decoding includes: for each estimated value X' (n) Perform space-time decoding, decoding into a high-dimensional symbol S' D .

4. The high-dimensional MIMO-OFDM implementation method based on spatial diversity as described in claim 1, characterized in that, In step S20, the space-time coding includes: performing space-time coding for every 2N high-dimensional symbols as a group, combining the corresponding dimensional coordinate components of every two adjacent high-dimensional symbols into a complex number to generate a space-time code array X. ST , where X ST It is a matrix with D rows and N columns. The element in the d-th row and n-th column of the matrix is ​​the d-th dimension coordinate component of the 2n-th high-dimensional symbol plus the d-th dimension coordinate component of the 2n+1-th high-dimensional symbol multiplied by the imaginary unit j, where 0≤d≤D-1, 0≤n≤N-1, N is the number of OFDM subcarriers, and j represents the imaginary number.

5. The high-dimensional MIMO-OFDM implementation method based on spatial diversity as described in claim 4, characterized in that, In step S50, the space-time decoding includes: converting each estimated value X' (n) The code is decoded into two high-dimensional symbols S' D That is, by X' (n) All real parts form a column vector, which is decoded into a high-dimensional symbol, represented by X'. (n) All the imaginary parts form a column vector, which is decoded into another high-dimensional symbol.

6. The high-dimensional MIMO-OFDM implementation method based on spatial diversity as described in claim 1, characterized in that, In step S10, the high-dimensional signal constellation diagram is represented as a two-dimensional matrix S. D The structure has dimensions of D rows and M columns, where the m-th D-dimensional symbol is represented as a column vector S. D (m) = [W0(m) W1(m) … W d (m)... W D-1 (m)] T T represents the transpose operation, W d Let d represent the d-th real coordinate component of the high-dimensional symbol, 0≤d≤D-1, 0≤m≤M-1.

7. The high-dimensional MIMO-OFDM implementation method based on spatial diversity as described in claim 1, characterized in that, In step S30, the length of the cyclic prefix is ​​greater than the maximum multipath delay of the wireless channel.

8. The high-dimensional MIMO-OFDM implementation method based on spatial diversity as described in claim 1, characterized in that, In step S50, the MIMO detection employs either the maximum likelihood detection algorithm or the minimum mean square error detection algorithm.

9. The high-dimensional MIMO-OFDM implementation method based on spatial diversity as described in claim 1, characterized in that, The high-dimensional signal constellation diagram is a D-dimensional M-ary signal constellation diagram, where D≥3 and M≥4.

10. A high-dimensional MIMO-OFDM system based on spatial diversity for implementing the method of any one of claims 1 to 9, characterized in that, Includes the sending end and the receiving end; The sending end includes: The serial-to-parallel conversion module is used to group the serial bit stream to be transmitted into parallel groups of k bits each, where k = log2M and M is the size of the high-dimensional signal constellation diagram. A high-dimensional signal mapper module is used to map k bits of each parallel group to a D-dimensional high-dimensional symbol, where D≥3; A high-dimensional signal space-time encoder module is used to perform space-time encoding on the high-dimensional symbols to generate a space-time code array; The N-point inverse fast Fourier transform module is used to perform inverse fast Fourier transform on each row vector of the space-time code array, converting the frequency domain signal into a time domain signal. The cyclic prefix module is used to add a cyclic prefix to the time-domain signal, and through N T N antennas transmit, where N T =D; The receiving end includes: The module for removing cyclic prefixes is used to process N. R The time-domain signal received by each receiving antenna is stripped of its cyclic prefix, where N R ≥N T ; The N-point Fast Fourier Transform module is used to perform Fast Fourier Transform on the time-domain signal after removing the cyclic prefix, converting the time-domain signal into a frequency-domain signal. The MIMO detector module is used to detect the frequency domain signal and obtain an estimate of the transmitted signal. A high-dimensional signal space-time decoder module is used to perform space-time decoding on the estimated value to recover the high-dimensional symbol; A high-dimensional signal demapping module is used to demap the high-dimensional symbol back to k parallel information bits; The parallel-to-serial conversion module is used to convert the k parallel information bits into a serial binary sequence to recover the original transmitted bit stream.

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