A pre-processing method for reducing peak-to-average ratio of MIMO-OFDM signal

Abstract

The application provides a pre-processing method for reducing the peak-to-average ratio of a MIMO-OFDM signal, comprising the following steps: S1, performing constellation point pre-expansion and beamforming on a frequency domain signal X og ; S2, obtaining a time domain signal x m corresponding to the frequency domain signal X m ; S3, obtaining a peak cancellation sequence y m ; S4, calculating a peak cancellation frequency domain signal carried at a reserved subcarrier set according to the peak cancellation sequence y m , performing least square approximation on a time domain signal c m corresponding to the peak cancellation frequency domain signal to obtain an optimal amplification coefficient and obtaining a final time domain signal after peak cancellation; S5, performing one-time clipping processing on the signal, performing Fourier transform to a frequency domain, performing beamforming inverse transform on the frequency domain signal, and performing constellation correction; and S6, inputting the signal into a MIMO system to obtain a transmission signal of each antenna, and determining whether the peak-to-average ratio requirement is met to determine whether to directly transmit or iterate again. The application can greatly reduce the calculation complexity while ensuring the BER performance.

Description

Technical Field

[0001] This invention relates to a preprocessing method for reducing the peak-to-average power ratio (PAPR) of MIMO-OFDM signals. Background Technology

[0002] Multiple-input multiple-output (MIMO) technology is considered one of the key technologies in 5G. Massive MIMO technology can be adapted to MIMO systems, thereby increasing the spatial freedom of the wireless channel and bringing higher data rates and transmission reliability. Orthogonal frequency division multiplexing (OFDM) is an important multi-carrier modulation technique that effectively solves the frequency-selective fading problem by decomposing a wideband channel into several independent narrowband channels. Combining OFDM technology with MIMO systems leverages the advantages of both, achieving faster communication rates and higher spectrum utilization. This system has been recognized as a reliable technology for future generations of wireless communication.

[0003] However, OFDM technology, as a multi-carrier modulation technique, superimposes multiple orthogonal subcarriers, leading to significant dynamic fluctuations in the envelope of the base station's transmitted signal, resulting in a high peak-to-average power ratio (PAPR). PAPR signals typically require transmission through linear power amplifiers, but these are expensive and require sophisticated manufacturing processes, resulting in substantial hardware costs. Conversely, transmitting PAPR signals through nonlinear power amplifiers introduces severe nonlinear distortion, causing signal aberration and significantly degrading system performance. J. Tellado's Tone Reservation (TR) technique can reduce the PAPR of individual antennas, but its PAPR suppression effect is not significant, and the data transmission rate is noticeably reduced. The Active Constellation Extension (ACE) algorithm proposed by BSKrongold and DLJones can significantly reduce the PAPR of a single-antenna system through multiple iterations. However, ACE in MIMO-OFDM systems requires beamforming and inverse transformation in each iteration, and its slow convergence speed leads to high computational complexity. Therefore, we need to use methods with faster convergence and lower computational complexity to reduce the peak-to-average power ratio (PAPR) of multi-user MIMO-OFDM systems. Summary of the Invention

[0004] The purpose of this invention is to propose a preprocessing method to reduce the peak-to-average power ratio (PAPR) of MIMO-OFDM signals, which can greatly reduce computational complexity while ensuring BER performance.

[0005] This invention is achieved through the following technical solution:

[0006] A preprocessing method for reducing the peak-to-average power ratio (PAPR) of MIMO-OFDM signals includes the following steps:

[0007] Step S1: Input signal S og After constellation point pre-spreading, signal S is obtained, and frequency domain signals on each antenna are obtained through beamforming, where the frequency domain signal on the m-th antenna is represented as X. m ;

[0008] Step S2: Convert the frequency domain signal X m The corresponding time-domain signal x is obtained by inverse fast Fourier transform. m ;

[0009] Step S3: Convert the time-domain signal x m Perform initial peak cancellation and obtain the peak cancellation sequence y m According to the peak cancellation sequence y m Calculate the peak cancellation frequency domain signal carried at the reserved subcarrier set. And the peak cancellation frequency domain signal The corresponding time-domain signal c m Perform a least squares approximation to obtain the optimal magnification factor. This optimal magnification factor will be utilized. Amplified time-domain signal With time-domain signal x m The summation yields the final time-domain signal after peak cancellation.

[0010] Step S4: Time-domain signal after peak cancellation Perform a clipping process, then perform a Fourier transform to the frequency domain, and then perform inverse beamforming transform on the frequency domain signal before constellation correction.

[0011] Step S5: Input the signal obtained in step S4 into the MIMO system to obtain the transmission signal of each antenna. Determine whether the peak-to-average power ratio (PAPR) requirement is met. If it is met, transmit directly; otherwise, return to step S1 for iteration.

[0012] Furthermore, in step S1, the input signal S og This is the frequency domain sequence after QAM modulation based on the original information sequence.

[0013] Furthermore, in step S2, according to the formula Performing an inverse fast Fourier transform yields the corresponding time-domain signal x. m , where x m(n), n=0,1,...,N-1 is the time-domain signal on the m-th antenna.

[0014] Furthermore, in step S3, the number L of peak signals to be canceled is determined, and the amplitudes of these L peak signals are reduced to amplitude A, where amplitude A is the amplitude of the signal second only to the smallest amplitude signal among the L peak signals, thus obtaining the peak cancellation sequence y. m for: Where n = 0, 1, ..., N-1.

[0015] 9. Further, in step S3, the peak cancellation frequency domain signal is calculated using the least squares method. in, Here is the inverse fast Fourier transform matrix corresponding to the reserved subcarrier positions, where, To reserve the position information of each subcarrier in the subcarrier set.

[0016] Furthermore, in step S3, the optimal magnification factor is obtained according to the following formula. And according to the formula For time-domain signal sequence c m Enlarge it, among which, For when y m The set of values ​​of n when (n) ≠ 0, c m (n) is the time-domain signal sequence c m The nth data.

[0017] Furthermore, in step S4, according to the formula For time domain signals Perform a clipping process, where A′ is the clipping threshold, and e jφ(n) For x m The phase of (n).

[0018] Furthermore, in step S4, according to the formula Perform inverse beamforming transform, where W + The pseudo-inverse matrix of the beamforming matrix, The time-domain signal after one clipping process The frequency domain signal after Fourier transform.

[0019] The present invention has the following beneficial effects:

[0020] 1. This invention improves a simplified TR algorithm based on the least squares approximation and uses this improvement to pre-reduce the peak-to-average power ratio (PAPR) of the MIMO-OFDM signal. Compared with the traditional TR algorithm, it can achieve the same PAPR suppression effect with fewer reserved subcarriers. Then, the traditional ACE algorithm is optimized by using the method of pre-expanding the original constellation points, which greatly speeds up the convergence speed of the algorithm and enhances the PAPR suppression effect in each iteration. According to the preprocessing method of this invention, a good PAPR suppression effect can be obtained by performing one preprocessing, which is equivalent to the PAPR suppression effect achieved by the traditional ACE algorithm in 8 iterations. In general, only two iterations according to the preprocessing method of this invention are needed to achieve the desired PAPR suppression effect, while the traditional ACE algorithm often requires as many as 30 iterations. It can be seen that this invention can greatly reduce the computational complexity while ensuring BER performance. Attached Figure Description

[0021] The present invention will now be described in further detail with reference to the accompanying drawings.

[0022] Figure 1 This is a flowchart of the present invention.

[0023] Figure 2 This is a system model diagram for using the present invention.

[0024] Figure 3 This is a model diagram of the preprocessing module of the present invention.

[0025] Figure 4 This is a schematic diagram of the constellation point pre-expansion of the present invention.

[0026] Figure 5 This is a schematic diagram illustrating the scalable region and constellation correction of the present invention.

[0027] Figure 6 The figure shows the simulation results of the cumulative distribution function (CCDF) curve of the PAPR signal in the MIMO-OFDM of this invention.

[0028] Figure 7 The figure shows the simulation results of the bit error rate performance curve of the system of the present invention. Detailed Implementation

[0029] In this embodiment, a typical multi-user MIMO-OFDM communication system is considered. The PAPR of the OFDM signal on each transmit antenna is defined as the ratio of the maximum power to the average power of the time-domain transmitted signal. x m (n) represents the time-domain transmitted signal, n = 1, 2, ..., N-1, m = 1, 2, ..., M, where N is the total number of subcarriers and M is the number of transmitting antennas. Other system parameters are: N scThe number of reserved subcarriers, Ω, represents the set of reserved subcarriers, containing N. sc The location information of each reserved subcarrier, where K is the number of users served by the system.

[0030] like Figures 1 to 3 As shown, the preprocessing method for reducing the peak-to-average power ratio (PAPR) of MIMO-OFDM signals includes the following steps:

[0031] Step S1: Input signal S og After constellation point pre-spreading, signal S is obtained, and frequency domain signals on each antenna are obtained through beamforming, where the frequency domain signal on the m-th antenna is represented as X. m , specifically:

[0032] Input signal S og The frequency domain sequence after QAM modulation based on each original information sequence is S. og =[s1,s2,…,s K ] T ,s1,s2,...,s K This refers to the data sent to each service user, which is a 1×N matrix, S og Let N be a K×N matrix, where N sc The signal on each sub-channel is 0, and it does not carry data signals;

[0033] For S og Each constellation point is multiplied by a pre-spreading factor β to obtain the pre-spread frequency domain sequence S. The choice of this pre-spreading factor β affects the PAPR suppression performance and the increase in average power. In this embodiment, through repeated experiments, a pre-spreading factor β = 1.15 was selected to achieve a balance between average power and PAPR suppression performance. The specific implementation of the pre-spread signal is shown in Figure 4. Its function is to ensure that more clipped constellation points can be retained within the expandable region during the constellation correction process in step S4. Figure 5 The shaded area in the image is the expandable area, thus minimizing PAPR.

[0034] The frequency domain sequence S is obtained by beamforming transformation according to the formula X = W·S to obtain the frequency domain sequence on the transmitting antenna, where W is the beamforming matrix.

[0035] Step S2: Convert the frequency domain signal X m The corresponding time-domain signal x is obtained by inverse fast Fourier transform. m Specifically, according to the formula Perform an inverse fast Fourier transform, where x m (n) is the time-domain signal on the m-th antenna, where n = 0, 1, ..., N-1.

[0036] Step S3: Convert the time-domain signal xm Perform initial peak cancellation and obtain the peak cancellation sequence y m According to the peak cancellation sequence y m Calculate the peak cancellation frequency domain signal carried at the reserved subcarrier set. And the peak cancellation frequency domain signal The corresponding time-domain signal c m Perform a least squares approximation to obtain the optimal magnification factor. This optimal magnification factor will be utilized. Amplified time-domain signal With time-domain signal x m The summation yields the final time-domain signal after peak cancellation.

[0037] Specifically, obtain the peak cancellation sequence y m First, determine the number L of peak signals to be canceled. Then, reduce the amplitude of these L peak signals to an amplitude A. This amplitude A is the second smallest amplitude among all the peak signals, second only to the smallest amplitude among these L. This yields the ideal peak cancellation sequence y. m for: Where n = 0, 1, ..., N-1; it can be seen that y m There are only L non-zero elements in (n);

[0038] Peak cancellation frequency domain signal calculated using least squares method in, Here is the inverse fast Fourier transform matrix corresponding to the reserved subcarrier positions, where, To reserve the position information of each subcarrier in the subcarrier set Ω;

[0039] In this embodiment, The values ​​are 1, 2, ..., N. sc The matrix is ​​then specifically:

[0040]

[0041] This peak cancellation frequency domain signal Perform an N-point IFFT to obtain the corresponding time-domain signal c. m , usually c m The amplitude will be much smaller than the ideal peak cancellation signal y. m Especially when N sc When the value is small, this is also a problem with the TR algorithm, requiring a trade-off between information transmission rate and PAPR suppression effect. To solve this problem, the time-domain signal c... m Amplify as follows: By amplifying the time-domain signal c m and peak cancellation signal ym The optimal magnification factor can be obtained by using the least squares approximation.

[0042] Seeking The problem can be formalized as: For when y m The set of values ​​for n when (n) ≠ 0 is obviously... There are L values ​​in total. Define a function. and make available And according to the formula For time-domain signal sequence c m To magnify, where c m (n) is the time-domain signal sequence c m The nth data.

[0043] Step S4: Time-domain signal after peak cancellation Perform a clipping process, then perform a Fourier transform to the frequency domain, and then perform inverse beamforming transform on the frequency domain signal before constellation correction.

[0044] Specifically, according to the formula For time domain signals Perform a clipping process, in which, P is the clipping threshold, γ is the threshold coefficient, and P is the threshold value. avg For average power, e jφ(n) For x m The phase of (n);

[0045] Due to the beamforming operation in step S1, the signals sent to each user have been coupled together, and their signal constellation diagram is consistent with the original frequency domain signal S. og The results are completely different, therefore the traditional ACE constellation correction rules cannot be directly implemented; instead, inverse beamforming transformation is required first. According to the formula... Perform inverse beamforming transform, where W + The pseudo-inverse matrix of the beamforming matrix, The time-domain signal after one clipping process The frequency domain signal after Fourier transform, and the constellation correction diagram are shown below. Figure 5 As shown, the frequency domain signal is obtained after constellation correction. It is worth mentioning that the constellation correction in this invention differs from traditional ACE in that the original constellation points in traditional ACE are vertices of the expandable region, while in this invention the original constellation points are inside the expandable region. This allows more clipped constellation points to remain within the expandable region, and some points that cannot be expanded in the traditional ACE algorithm (such as point B and B) can also be included. mod The point can also be extended in this invention.

[0046] Step S5: Input the signal obtained in step S4 into the MIMO system to obtain the transmitted signals of each antenna. Determine whether the peak-to-average power ratio (PAPR) requirement is met. If it is, transmit directly; otherwise, return to step S1 for iteration. The process of determining whether the PAPR requirement is met is existing technology.

[0047] Figure 6 The simulation conditions are: total number of subcarriers N = 1024, QPSK modulation is used, and the number of reserved subcarriers N sc =64, transmit antenna M=6, single receive antenna user K=4, peak cancellation quantity L=20, clipping threshold coefficient γ=4dB, pre-spread coefficient β=1.15. Figure 6 The x-axis PAPR0 is a threshold value in dB, and the y-axis is the complementary cumulative distribution function (CCDF) of PAPR, which is defined as the probability that PAPR exceeds the set threshold PAPR0. Simulation experiments compare the PAPR of the original multi-user MIMO-OFDM system, the traditional ACE method, the traditional TR method, and the multi-user MIMO-OFDM signal using the present invention at different iteration numbers.

[0048] Depend on Figure 6 As can be seen, this invention can effectively suppress PAPR of multi-user MIMO-OFDM signals. Compared with the original MIMO-OFDM signal, the PAPR suppression effect of one iteration exceeds 5dB, which is equivalent to the PAPR suppression performance of the traditional ACE algorithm after 8 iterations; the PAPR suppression effect of two iterations exceeds 6.5dB, which is equivalent to the PAPR suppression performance of the traditional ACE algorithm after 30 iterations; this invention can achieve a PAPR suppression gain of 4.5dB compared with the traditional TR method; and compared with the existing ACE method, it can achieve the same performance gain with less computational complexity.

[0049] Figure 7 Simulation conditions and Figure 6 The graph is the same, with the horizontal axis representing the signal-to-noise ratio (SNR) and the vertical axis representing the system's BER performance. Simulation experiments compared the BER performance of the original multi-user MIMO-OFDM system, the system using the traditional ACE method with 8 iterations, and the system using the method of this invention with 1 iteration.

[0050] Depend on Figure 7As can be seen, the BER performance of the method proposed in this invention is almost identical to that of the traditional ACE algorithm, and both are slightly better than the original multi-user MIMO-OFDM system. This is because both the algorithm proposed in this invention and the traditional ACE algorithm extend the constellation points outward, which leads to an increase in the average power of the transmitted signal; compared to the traditional ACE algorithm, the algorithm proposed in this invention achieves a slightly smaller increase in average power while maintaining the same performance.

[0051] The biggest advantage of the algorithm proposed in this invention compared to the traditional ACE algorithm is its faster convergence speed, thereby significantly reducing computational complexity. Computational complexity is usually measured by the number of complex multiplications. The computational complexity analysis of the algorithm proposed in this invention and the traditional ACE algorithm is as follows:

[0052] In each iteration of the traditional ACE algorithm, the operations required on each antenna are clipping, IFFT / FFT, and beamforming and its inverse transform; the computational complexities required are N, Nlog2N, and KN, respectively. Therefore, the total complexity required by the traditional ACE algorithm is I×(MN+2MNlog2N+2KMN), where I is the number of iterations.

[0053] The algorithm proposed in this invention performs operations similar to traditional ACE, so each antenna in each iteration also requires (MN + 2MNlog2N + 2KMN) complex multiplication operations. In addition, this invention also includes pre-spreading operations and an LSA-STR module, which requires an additional (LMN) sc +3LM+MN sc ) complex multiplication operations, where L, N sc The value is much smaller than that, and the total complexity of the algorithm proposed in this invention is...

[0054] I×(MN+2MNlog2N+2KMN+LMN sc +3LM+MN sc ).

[0055] Although the computational complexity of the algorithm proposed in this invention is higher than that of the traditional ACE algorithm in each iteration, this invention can achieve a good PAPR suppression gain with very few iterations, and L,N scThe value of is much smaller than N. Therefore, in the algorithm proposed in this invention, the increase in computational complexity for each iteration is not significant compared to the traditional ACE algorithm, and the total computational complexity is much smaller than that of the traditional ACE algorithm. When comparing the algorithm proposed in this invention after 1 iteration with the traditional ACE algorithm after 8 iterations, the algorithm proposed in this invention requires 83,440 complex multiplications, while the traditional ACE algorithm requires 622,592 complex multiplications. The computational complexity of the algorithm proposed in this invention is only 13.4% of that of the traditional ACE algorithm. When comparing the algorithm proposed in this invention after 2 iterations with the traditional ACE algorithm after 30 iterations, the algorithm proposed in this invention requires 166,880 complex multiplications, while the traditional ACE algorithm requires 2,334,720 complex multiplications. The computational complexity of the algorithm proposed in this invention is only 7.2% of that of the traditional ACE algorithm.

[0056] comprehensive Figure 6 , Figure 7 As analyzed above, the method of this invention achieves better PAPR suppression compared to the traditional TR method; compared to the traditional ACE algorithm, it achieves the same performance gain with fewer iterations and lower computational complexity, without sacrificing BER performance. This is because the LSA-STR algorithm (least squares approximation-simplified TR algorithm) is used pre-emptively to reduce the signal PAPR, effectively reducing the maximum amplitude of the time-domain transmitted signal and the number of symbols with large amplitudes. Furthermore, the original constellation points are pre-expanded, resulting in a smaller distribution radius of the clipped constellation points during constellation correction, leaving more clipped constellation points within the expandable region, thus achieving better PAPR suppression performance. In addition, the smaller clipping amplitude leads to a smaller increase in the average signal power. With the same maximum amplitude of the clipped signal, the signal PAPR of this invention is lower, which is beneficial for improving the efficiency of the power amplifier. In practical systems, system parameters such as the peak cancellation quantity L, clipping threshold γ, and pre-expansion coefficient β can be flexibly modified according to different scenario requirements to achieve different performance emphases.

[0057] The above description is merely a preferred embodiment of the present invention and should not be construed as limiting the scope of the present invention. All equivalent changes and modifications made in accordance with the scope of the patent application and the contents of the specification of the present invention should still fall within the scope of the patent of the present invention.

Claims

1. A preprocessing method for reducing the peak-to-average power ratio (PAPR) of MIMO-OFDM signals, characterized in that: Includes the following steps: Step S1: Input signal Signal obtained after constellation point pre-expansion And the frequency domain signal on each antenna is obtained through beamforming, where the first... The frequency domain signal on the root antenna is represented as ; Step S2: Convert the frequency domain signal The corresponding time-domain signal is obtained by inverse fast Fourier transform. ; Step S3: Convert the time-domain signal Perform initial peak cancellation and obtain peak cancellation sequence According to the peak cancellation sequence Calculate the peak cancellation frequency domain signal carried at the reserved subcarrier set. And cancel the peak frequency domain signal Corresponding time domain signal Perform a least squares approximation to obtain the optimal magnification factor. This optimal magnification factor will be utilized. Amplified time-domain signal With time domain signal The summation yields the final time-domain signal after peak cancellation. ; Step S4: Time-domain signal after peak cancellation Perform a clipping process, then perform a Fourier transform to the frequency domain, and then perform inverse beamforming transform on the frequency domain signal before constellation correction. Step S5: Input the signal obtained in step S4 into the MIMO system to obtain the transmitted signal of each antenna. Determine whether the peak-to-average power ratio requirement is met. If it is met, transmit directly; otherwise, return to step S1 for iteration. In step S1, for Each constellation point in the array is multiplied by a pre-expansion factor. Obtain the pre-extended frequency domain sequence Pre-expansion coefficient ; In step S4, according to the formula For time domain signals Perform a clipping process, in which, For the clipping threshold, for phase, For the first The time-domain signal on the root antenna, This represents the total number of subcarriers.

2. The preprocessing method for reducing the peak-to-average power ratio of MIMO-OFDM signals according to claim 1, characterized in that: In step S1, the input signal This is the frequency domain sequence after QAM modulation based on the original information sequence.

3. The preprocessing method for reducing the peak-to-average power ratio of MIMO-OFDM signals according to claim 2, characterized in that: In step S2, according to the formula Performing an inverse fast Fourier transform yields the corresponding time-domain signal. ,in, For the first The time-domain signal on the root antenna.

4. A preprocessing method for reducing the peak-to-average power ratio of MIMO-OFDM signals according to claim 1, 2, or 3, characterized in that: In step S3, the number of peak signals that need to be canceled is determined. , will this The amplitude of the peak signal decreases to the amplitude. that magnitude Second only to that The amplitude of the smallest amplitude signal among the peak signals is used to obtain the peak cancellation sequence. for: ,in, .

5. A preprocessing method for reducing the peak-to-average power ratio of MIMO-OFDM signals according to claim 1, 2, or 3, characterized in that: In step S3, the peak cancellation frequency domain signal is calculated using the least squares method. : ,in, Here is the inverse fast Fourier transform matrix corresponding to the reserved subcarrier positions, where, To reserve the position information of each subcarrier in the subcarrier set.

6. A preprocessing method for reducing the peak-to-average power ratio of MIMO-OFDM signals according to claim 1, 2, or 3, characterized in that: In step S3, the optimal magnification factor is obtained according to the following formula. : And according to the formula For time-domain signal sequences Enlarge it, among which, For when hour The set of possible values, Time-domain signal sequence The Data points.

7. A preprocessing method for reducing the peak-to-average power ratio of MIMO-OFDM signals according to claim 1, 2, or 3, characterized in that: In step S4, according to the formula Perform inverse beamforming transform, where, The pseudo-inverse matrix of the beamforming matrix, The time-domain signal after one clipping process The frequency domain signal after Fourier transform.

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