A method for suppressing OTFS peak-to-average power ratio using limiting logarithmic root compression

Abstract

The present invention discloses an OTFS peak-to-average power ratio suppression method using limiting logarithmic root compression, which relates to the field of communication technology and includes the following steps: step 1, obtaining a DD domain signal and performing an IDZT transformation on it to obtain a time domain signal; step 2, performing pulse shaping on the time domain signal through a transmitting end to obtain a time domain pulse signal; step 3, performing limiting processing on the time domain pulse signal to obtain a limiting signal and obtain limiting noise; step 4, performing logarithmic root compression on the limiting noise to obtain compressed noise; step 5, adding the logarithmic root compressed limiting noise to the limiting signal to obtain a corrected signal; step 6, transmitting the corrected signal to a digital-to-analog converter (DA) for transmission. The present invention suppresses the OTFS peak-to-average power ratio through a correspondingly designed CLRC algorithm, and effectively simplifies the number of complex multiplications and additions, thereby reducing the communication calculation burden.

Description

Technical Field

[0001] The invention relates to the field of communication technology, and in particular to an OTFS peak-to-average power ratio suppression method using limiting logarithmic root compression. Background Art

[0002] As one of the core technologies of the fourth generation of mobile communications (4G) and the fifth generation of mobile communications (5G), orthogonal frequency division multiplexing (OFDM) technology has been widely used due to its efficient spectrum utilization and anti-multipath interference capabilities. However, OFDM technology's sensitivity to Doppler shift limits its application in high-speed mobile scenarios. With the continuous development of mobile communication technology, especially the increasing demand for high-speed mobile users and massive MIMO technology in the sixth generation of mobile communications (6G), the limitations of traditional OFDM technology have become increasingly obvious. For this reason, orthogonal time-frequency-space (OTFS) modulation technology came into being. OTFS can effectively deal with Doppler shift and time-varying channel problems in high-speed mobile environments by performing two-dimensional modulation in the delay-Doppler domain, providing important technical support for future 6G systems.

[0003] Traditional OTFS systems are mainly implemented using discrete symplectic finite Fourier transform (ISFFT) and Heisenberg transform (HT). Although they perform well in delay-Doppler domain modulation, their implementation complexity is relatively high, especially in large-scale multi-user scenarios, where computing resources and real-time performance become bottlenecks. In addition, OTFS signals have a high peak-to-average power ratio (PAPR), which can easily cause the power amplifier to enter the nonlinear region, thereby causing signal distortion and affecting system performance. In order to solve this problem, scholars have proposed a variety of PAPR suppression methods, but these methods are often accompanied by increased computational complexity and loss of system performance while reducing PAPR. The existing OTFS system PAPR suppression methods based on two-step conversion have the following problems:

[0004] (1) Selective mapping (SLM) and partial transmission sequence (PTS) methods reduce the PAPR value by optimizing the signal phase or selecting the candidate signal with the lowest PAPR. Although they can reduce the PAPR to a certain extent, they will increase the system overhead and computational complexity, and may affect the system performance;

[0005] (2) Precoding, DFT spread spectrum and constellation expansion technology reduce the PAPR value through precoding, DFT spread spectrum and constellation expansion technology, but it requires multiple Fourier transforms, resulting in a significant increase in the amount of complex multiplication and addition operations, and high computational complexity. In addition, these methods may cause certain distortion to the signal and rely on the statistical characteristics of the modulated signal, and have poor adaptability;

[0006] (3) Iterative clipping filtering (ICF) and hybrid optimization algorithms reduce PAPR by repeatedly filtering out noise through iterative clipping filtering, but their computational complexity is high and may introduce additional signal distortion. Hybrid optimization algorithms (such as bacterial foraging algorithms) reduce PAPR by iteratively searching for the optimal phase combination, but their computational complexity is high and is not conducive to engineering implementation;

[0007] (4) Law compression technology and error function compression technology directly compress the OTFS signal. Although they can reduce PAPR, they will lose the system's bit error rate (BER) performance and affect the communication quality. Summary of the invention

[0008] The present invention aims to provide an OTFS peak-to-average power ratio suppression method using limiting logarithmic root compression to solve at least one of the above problems.

[0009] The present invention is achieved through the following technical solutions:

[0010] A method for suppressing OTFS peak-to-average power ratio by limiting logarithmic root compression comprises the following steps:

[0011] Step 1: Obtain a DD domain signal and perform an IDZT transform on it to obtain a time domain signal;

[0012] Step 2: The time domain signal is pulse shaped at the transmitting end to obtain a time domain pulse signal;

[0013] Step 3, performing a limiting process on the time domain pulse signal to obtain a limiting signal and obtain limiting noise;

[0014] Step 4, performing logarithmic root compression on the limiting noise to obtain compressed noise;

[0015] Step 5, adding the compressed noise obtained by logarithmic root compression to the limited signal to obtain a corrected signal;

[0016] Step six, the corrected signal is sent to the digital-to-analog converter (DA) for transmission.

[0017] The present invention first converts the delay-Doppler (DD) domain signal into a time domain signal through the inverse discrete Zak transform (IDZT), simplifies the complex ISFFT and HT two-step operations in the traditional OTFS system, reduces the number of complex multiplications and additions, and reduces the computational burden. Then, the time domain signal is pulse shaped to ensure the waveform integrity of the signal during transmission. Then, the limiting noise is extracted through limiting processing to avoid the distortion problem caused by directly compressing the signal. The limiting noise is then logarithmically compressed to further reduce the PAPR, while reducing the impact on the signal itself and maintaining the integrity of the signal. Finally, the compressed noise is superimposed on the limiting signal to form a corrected signal, ensuring the low PAPR characteristics of the transmitted signal. The entire design combines limiting and logarithmic root compression to not only improve the PAPR suppression effect, but also reduce the computational complexity, and is particularly suitable for resource-constrained communication systems.

[0018] The advantage of the present invention is that it replaces the traditional two-step operation with a one-step IDZT transformation, greatly reducing the number of complex multiplications and additions, significantly reducing the computational complexity, and is particularly suitable for resource-constrained communication systems; the combination of limiting and logarithmic root compression effectively reduces the PAPR of the OTFS signal, and only compresses the limiting noise, avoiding the distortion problem caused by direct signal processing and maintaining the integrity of the signal. Finally, the PAPR suppression effect of the present invention under high signal-to-noise ratio conditions is better than that of the traditional simple limiting filter (SCF) and μ-law compression methods, and has little effect on the bit error rate (BER), and can maintain high system performance while reducing PAPR. This low complexity and high performance feature makes the CLRC algorithm have broad application prospects in 6G communication systems.

[0019] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0020] 1. The implementation complexity of the limited logarithmic root compression (CLRC) algorithm proposed in the present invention is significantly lower than that of the traditional OTFS system PAPR suppression method; the traditional method usually uses two-step operations of discrete sigmoid finite Fourier transform (ISFFT) and Heisenberg transform (HT) to realize the modulation and demodulation of OTFS signals, which requires multiple complex multiplication and addition operations, resulting in high computational complexity. The present invention uses a one-step operation of discrete Zak transform (DZT), which simplifies the signal processing process and reduces the number of complex multiplication and addition. Especially when M=256 and N=64, the computational complexity of the CLRC algorithm is much lower than that of traditional methods such as selective mapping (SLM) and partial transmission sequence (PTS). In addition, the CLRC algorithm does not need to perform complex operations such as Wigner transform (WT) and sigmoid Fourier transform (SFFT) after limiting, which further reduces the computational burden. This low-complexity implementation makes the CLRC algorithm more suitable for application in practical engineering, especially in resource-constrained communication systems;

[0021] 2. The present invention significantly improves the peak-to-average power ratio (PAPR) suppression effect of the OTFS system through a combination of limiting and logarithmic root compression; traditional PAPR suppression methods, such as iterative limiting filtering (ICF) and μ-law compression, can reduce PAPR to a certain extent, but often cause signal distortion, and rely on the statistical characteristics of the modulated signal, and have poor adaptability. After limiting, the CLRC algorithm only performs logarithmic root compression on the limiting noise instead of directly compressing the signal, thereby reducing signal distortion. Logarithmic root compression can more effectively control the PAPR of the limiting noise, so that the final transmitted signal has a lower PAPR value. Through comparative analysis of the complementary cumulative distribution function (CCDF), the CLRC algorithm is superior to the traditional simple limiting filtering (SCF) and μ-law compression methods in PAPR suppression performance, especially under high signal-to-noise ratio conditions, the PAPR suppression effect of the CLRC algorithm is more obvious;

[0022] 3. In the process of PAPR suppression, the present invention effectively reduces signal distortion by combining limiting and logarithmic root compression. Traditional PAPR suppression methods, such as iterative limiting filtering (ICF) and μ-law compression, usually directly compress or filter the OTFS signal, which will cause nonlinear distortion of the signal and affect the bit error rate (BER) performance of the system. However, after limiting, the CLRC algorithm only performs logarithmic root compression on the limiting noise instead of directly processing the signal itself, thereby preserving the integrity of the original signal to the maximum extent. In addition, the CLRC algorithm uses a more sophisticated logarithmic root compression function in the compression process, which can better control the amplitude and phase of the limiting noise and further reduce signal distortion. Experimental results show that the CLRC algorithm has little effect on the bit error rate of the signal while reducing the PAPR, and can achieve effective PAPR suppression without significantly reducing system performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The drawings described herein are used to provide a further understanding of the embodiments of the present invention, constitute a part of this application, and do not constitute a limitation of the embodiments of the present invention. In the drawings:

[0024] Figure 1 This is the block diagram of the CLRC algorithm of this embodiment;

[0025] Figure 2 This is a schematic diagram of the PAPR process of the DZT-OTFS signal by the CLRC algorithm of this embodiment;

[0026] Figure 3 This is a schematic diagram of algorithm complexity comparison under specific parameters of this embodiment;

[0027] Figure 4 This is a PAPR performance comparison chart of the CLRC method of this embodiment and the selected comparison algorithm. DETAILED DESCRIPTION

[0028] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with embodiments and drawings. The exemplary embodiments of the present invention and their description are only used to explain the present invention and are not intended to limit the present invention.

[0029] like Figures 1 to 4 As shown, this embodiment relates to an OTFS peak-to-average power ratio suppression method using limited logarithmic root compression, which includes a low-complexity CLRC algorithm to reduce the PAPR value of the DZT-OTFS (OTFS system peak-to-average power ratio suppression technology using discrete Zak transform DZT in one step) system (see Figure 1); The method is used to suppress the peak-to-average power ratio (PAPR) in an orthogonal time-frequency-space (OTFS) system. OTFS technology is proposed to address the limitations of traditional orthogonal frequency division multiplexing (OFDM) technology in high-speed mobile environments, and is particularly important in sixth-generation mobile communication (6G) systems. However, OTFS signals have high PAPR in the time domain, which can cause nonlinear distortion of the power amplifier and affect the performance of the communication system. Existing PAPR suppression methods usually have high computational complexity or cause signal distortion. The present invention effectively reduces the PAPR through innovative limiting and logarithmic root compression techniques while maintaining low computational complexity and signal quality.

[0030] The CLRC algorithm performs limiting processing on the OTFS signal, then performs logarithmic root compression on the noise after limiting, and finally superimposes the compressed noise on the limiting signal to form the final transmission signal. The specific steps include: first, performing an inverse discrete Zak transform (IDZT) on the signal in the delay-Doppler (DD) domain to convert it into a time domain signal; then, performing limiting processing on the time domain signal to extract the limiting noise; then, performing logarithmic root compression on the limiting noise; finally, superimposing the compressed noise on the limiting signal to form the final transmission signal. Compared with the traditional PAPR suppression method, the present invention simplifies the signal processing process and reduces the computational complexity through a one-step IDZT transformation. At the same time, by compressing the limiting noise instead of directly compressing the signal, signal distortion is avoided, thereby improving the PAPR suppression effect and adaptability of the system.

[0031] Specifically, the signal processing steps of the proposed CLRC algorithm to suppress the PAPR of the DZT-OTFS system are as follows (see Figure 2 ):

[0032] (1) Obtaining DD domain signal , perform IDZT transformation according to the following method A1 to obtain the time domain signal .

[0033] (A1)

[0034] Where M and N represent the number of time Doppler grids and time delay grids respectively, and they satisfy: ; , , ;

[0035] (2) Time domain signal After pulse shaping at the transmitting end, the time domain pulse signal is obtained .

[0036] (A2)

[0037] In the formula, Indicates about The root raised cosine filter function, where , .

[0038] (3) According to equation A3, for the time domain pulse signal Perform limiting processing to obtain the limited signal .

[0039] (A3)

[0040] Here and Respectively represent the preset threshold value and signal The phase of The threshold is usually set to ,here and Represent the limiting ratio and signal The average power.

[0041] (4) According to the following formula A4, the limiting noise is obtained .

[0042] (A4)

[0043] (5) According to the following equations A5 and A6, the limiting noise Perform logarithmic root compression to obtain compressed noise The logarithmic root compressed limiting noise can be expressed as

[0044] (A5)

[0045] Here the logarithmic root compression function Defined as

[0046] (A6)

[0047] In formula A6 is a compression parameter, usually ranging from 5 to 25, which determines the compression level of the limiting noise. It is also a compression parameter, usually varying between 0 and 1, which determines the PAPR suppression capability of limiting noise.

[0048] (6) Compression noise obtained by logarithmic root compression is added to the clipping signal The corrected signal is obtained .

[0049] (A7)

[0050] (7) Signal Sent to the digital-to-analog converter (DA) for transmission.

[0051] The limited logarithmic root compression (CLRC) algorithm gradually realizes the effective suppression of the peak-to-average power ratio (PAPR) of the OTFS system, while significantly reducing the computational complexity. The algorithm described in the embodiment converts the delay-Doppler (DD) domain signal into a time domain signal through the inverse discrete Zak transform (IDZT), simplifies the complex ISFFT and HT two-step operations in the traditional OTFS system, reduces the number of complex multiplications and additions, and reduces the computational burden. Next, the time domain signal is pulse shaped and limited to extract the limiting noise, avoiding the distortion problem caused by directly compressing the signal. Then, by performing logarithmic root compression on the limiting noise, the PAPR is further reduced, while reducing the impact on the signal itself and maintaining the integrity of the signal. Finally, the compressed noise is superimposed on the limiting signal to form a corrected signal, ensuring the low PAPR characteristics of the transmitted signal. The entire design not only improves the PAPR suppression effect, but also reduces the computational complexity through the combination of limiting and logarithmic root compression, and is particularly suitable for resource-constrained communication systems.

[0052] In addition, the complexity of the complex multiplication and complex addition calculations of the CLRC algorithm is analyzed. Parameters are set and the complexity of each PAPR suppression method is compared with the complexity of the CLRC algorithm described in this embodiment (see Figure 3 ), by comparison, it can be seen that the limited logarithmic root compression (CLRC) algorithm of this embodiment is significantly superior to the traditional OTFS system PAPR suppression method in terms of computational complexity, especially in terms of the number of complex multiplications and adders used. The traditional method usually uses two-step operations of discrete sigmoid finite Fourier transform (ISFFT) and Heisenberg transform (HT) to realize the modulation and demodulation of OTFS signals, which requires multiple complex multiplications and additions, resulting in high computational complexity. In contrast, this embodiment simplifies the signal processing process through a one-step inverse discrete Zak transform (IDZT) and reduces the number of complex multiplications and additions. Specifically, when M=256 and N=64, the number of complex multiplications of the CLRC algorithm is only about one-tenth of the traditional selective mapping (SLM) and partial transmission sequence (PTS) methods, and the number of additions is also significantly reduced. In addition, the CLRC algorithm does not need to perform complex operations such as Wigner transform (WT) and sigmoid Fourier transform (SFFT) after limiting, which further reduces the computational burden. This low-complexity implementation makes the CLRC algorithm more suitable for application in practical engineering, especially in resource-constrained communication systems, and can effectively reduce the computational burden and power consumption of hardware implementation.

[0053] In wireless communication systems, the complementary cumulative distribution function (CCDF) is usually used to represent the statistical characteristics of the system PAPR. The present invention also uses CCDF to evaluate the improvement of the precoded DFT spread spectrum on the PAPR of the DZT-OTFS system. In order to study the influence of the modulation mode on the PAPR, the PAPR suppression performance of the CLRC method proposed in the present invention (see Figure 4 ); The limited logarithmic root compression (CLRC) algorithm described in this embodiment has significant advantages in performance and complexity. First, the algorithm replaces the complex ISFFT and HT two-step operations in the traditional OTFS system with an inverse discrete Zak transform (IDZT) one-step operation, greatly reducing the number of complex multiplications and additions, and significantly reducing the computational complexity. When M=256 and N=64, the computational complexity of the CLRC algorithm is much lower than that of traditional selective mapping (SLM) and partial transmission sequence (PTS) methods, and is particularly suitable for resource-constrained communication systems. Secondly, the CLRC algorithm effectively reduces the peak-to-average power ratio (PAPR) of the OTFS signal through a combination of limiting and logarithmic root compression, and only compresses the limiting noise, avoiding the distortion problem caused by direct signal processing and maintaining the integrity of the signal. The graphical results show that the PAPR suppression effect of the CLRC algorithm under high signal-to-noise ratio conditions is better than that of the traditional simple limiting filter (SCF) and μ-law compression methods, and has little effect on the bit error rate (BER), and can maintain high system performance while reducing the PAPR.

[0054] In addition, Figure 4 In the figure, the horizontal axis PAPR (dB) represents the peak-to-average power ratio, and the vertical axis CCDF represents the complementary cumulative distribution function, that is, the probability that the PAPR value exceeds the threshold value.

[0055] It should be noted that Figure 3 In, the SCF method is the selected carrier method, and the μ-LC method is the μ-law compression method; Figure 4 In the figure, CCDF is the complementary cumulative distribution function, which is used to express the probability that a random variable is greater than a certain value.

[0056] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. An OTFS peak-to-average power ratio suppression method using limiting logarithmic root compression, characterized in that: The following steps are included: Step 1: Obtain a DD domain signal and perform an IDZT transform on it to obtain a time domain signal; Step 2: The time domain signal is pulse shaped at the transmitting end to obtain a time domain pulse signal; Step 3, performing a limiting process on the time domain pulse signal to obtain a limiting signal and obtain limiting noise; Step 4, performing logarithmic root compression on the limiting noise to obtain compressed noise; Step 5, adding the compressed noise obtained by logarithmic root compression to the limited signal to obtain a corrected signal; Step six, the corrected signal is sent to a digital-to-analog converter (DA) for transmission; in, In step 3, the time domain pulse signal is recorded as , using the formula Perform limiting processing to obtain the limited signal , and according to the formula Calculate the limiting noise ; In the formula, and Respectively represent the preset threshold value and time domain pulse signal The phase of , M and N represent the number of Doppler grids and delay grids respectively; the threshold is set to , and Represent the limiting ratio and signal The average power of, j is an imaginary unit; In step 4, the limiting noise Logarithmic root compression is performed using the following two formulas to obtain the compressed noise: : ， ， in, and These are compression parameters. The range is between 5 and 25. The range is between 0 and 1. For limiting noise The logarithmic root compression function of .

2. The OTFS peak-to-average power ratio suppression method using limiting logarithmic root compression as claimed in claim 1, characterized in that: The DD domain signal in step 1 is recorded as , which performs IDZT transformation according to the following formula to obtain the time domain signal : ， In the formula, ; , , .

3. The OTFS peak-to-average power ratio suppression method using limiting logarithmic root compression as claimed in claim 2, characterized in that: In step 2, the time domain signal Pulse shaping is performed according to the following formula to obtain a time domain pulse signal : ， In the formula, Indicates about The root raised cosine filter function, , .

4. The OTFS peak-to-average power ratio suppression method using limiting logarithmic root compression as claimed in claim 1, characterized in that: Compression noise obtained by logarithmic root compression , is added to the limiting signal using the following calculation formula The corrected signal is obtained : .

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