A PAPR suppression method, device, storage medium and equipment

Abstract

The application discloses a PAPR suppression method, device, storage medium and equipment, the subcarriers of the radar communication integrated system are divided into data subcarriers and blank subcarriers, frequency domain data containing the blank subcarriers is acquired, the weighted least square method is used to improve the suppression effect on the PAPR, the performance of the radar communication integrated system is ensured, the data subcarriers are divided into radar subcarriers and communication subcarriers, the radar subcarriers are used to reduce the PAPR of the integrated signal, and flexible subcarrier adjustment can be carried out according to different system requirements and performance indexes, so that the best resource allocation scheme is obtained.

Description

Technical Field

[0001] This invention relates to a PAPR suppression method, apparatus, storage medium, and device, belonging to the field of radar-communication integration technology. Background Technology

[0002] PAPR (Peak to Average Power Ratio) is a metric used to measure the difference between the peak power and average power of a signal. In communication and wireless transmission systems, signals are often transmitted in the form of complex waveforms, such as sine waves, amplitude-modulated signals, and quadrature amplitude-modulated signals. During transmission, the peak power of these signals usually changes with the instantaneous amplitude of the signal, resulting in a relatively high peak-to-average power ratio.

[0003] A higher PAPR signal will result in a larger dynamic range during transmission, which may introduce nonlinear distortion in the power amplifier and limit the system's performance. Therefore, PAPR is an important performance parameter that needs to be considered in the design and optimization of wireless communication systems.

[0004] In integrated radar and communication systems, when radar and communication share the same spectrum resources for wireless communication, the PAPR problem may lead to a degrade in system performance. Specifically, a high PAPR signal may introduce nonlinear distortion into the power amplifier, resulting in problems such as increased bit error rate and reduced dynamic range. Summary of the Invention

[0005] This invention provides a PAPR suppression method, apparatus, storage medium, and device, which solves the problem of high PAPR signal during communication in integrated radar and communication systems.

[0006] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows:

[0007] A PAPR suppression method, comprising:

[0008] The subcarriers of the radar-communication integrated system are divided into data subcarriers and blank subcarriers to obtain frequency domain data Y. The frequency domain data Y is the radar-communication integrated frequency domain data, which includes radar data subcarriers, communication data subcarriers, and blank subcarriers. The radar data subcarriers are the data subcarriers that modulate radar data, and the communication data subcarriers are the data subcarriers that modulate communication data.

[0009] Perform an IFFT transform on the frequency domain data Y to obtain the time domain data y;

[0010] A subcarrier reservation method based on weighted least squares is used to iteratively smooth the time-domain data y, and the smoothed time-domain data is converted into a signal for use in the radar-communication integrated system.

[0011] The formula for frequency domain data Y is:

[0012] Y = G + H;

[0013] In the formula, G is the frequency domain signal of the data subcarrier, the length of G is N, each position corresponds to a subcarrier, if the (k+1)th position corresponds to a data subcarrier, then the (k+1)th element is G(k), if the (k+1)th position corresponds to a blank subcarrier, then the (k+1)th element is 0; G = G1 + G2, G1 is radar data, G2 is communication data;

[0014] H is the frequency domain signal of the blank subcarrier. The length of H is N. Each position corresponds to a subcarrier. If the (k+1)th position corresponds to a data subcarrier, then the (k+1)th element is 0. If the (k+1)th position corresponds to a blank subcarrier, then the (k+1)th element is H(k).

[0015] In the process of iteratively smoothing the time-domain data y using a subcarrier reservation method based on weighted least squares, each iteration of peak smoothing includes:

[0016] 1) Based on the time-domain data y of the i-th iteration i Calculate the peak-shaving threshold for the i-th iteration;

[0017] 2) If the time-domain data y i If the peak value is less than or equal to the peak reduction threshold, then no adjustment is needed to the time-domain data y. i Processing is performed, and the iterative peak reduction ends;

[0018] If the time-domain data y i The peak value is greater than the peak reduction threshold. Based on the peak reduction threshold, the time domain data y is adjusted. i Peak clipping is performed to obtain a time-domain limited signal. Go to 3);

[0019] 3) Based on the time-domain data y i and time-domain limiting signal Calculate the initial peak clipping noise data f i ;

[0020] 4) For the initial peak-shaving noise data f i Perform an FFT transformation to obtain the initial peak-shaving noise data f. i Frequency domain noise data F i ;

[0021] 5) Retain frequency domain noise data F i Data on the blank subcarrier will be converted into frequency domain noise data F. i The data at the mid-data subcarrier position is cleared to obtain new frequency domain peak-clipping data CC. i ;

[0022] 6) Crop clipping of new frequency domain data CC i Perform IFFT transformation to obtain time-domain peak-shaving data c i ;

[0023] 7) Based on time-domain peak-shaving data c i and initial peak clipping noise data f i The weighted least squares method is used to calculate the optimal iteration coefficients for the i-th iteration;

[0024] 8) Based on the optimal iteration coefficients of the i-th iteration and the time-domain peak-shaving data c i and the time-domain data y of the i-th iteration i Calculate the time-domain data y for the (i+1)th iteration. i+1 .

[0025] Based on the time-domain data y of the i-th iteration i The peak-shaving threshold for the i-th iteration is calculated using the following formula:

[0026] A i =R i ·E[y i ];

[0027] In the formula, A i R is the peak-shaving threshold for the i-th iteration. i Let E[y] be the threshold amplification factor for the i-th iteration. i ] represents time-domain data y i The average amplitude.

[0028] Based on the peak reduction threshold, the time-domain data y i Peak clipping is performed to obtain a time-domain limited signal. The formula is:

[0029]

[0030] In the formula, The time-domain limiting signal for the i-th iteration The (n+1)th data in the array, y i (n) represents the time-domain data y for the i-th iteration. i The (n+1)th data in the sequence;

[0031] Based on time-domain data y i and time-domain limiting signal Calculate the initial peak clipping noise data f i The formula is:

[0032]

[0033] Among them, f i(n) represents the initial peak-shaving noise data f in the i-th iteration. i The (n+1)th data in the dataset.

[0034] Preserve frequency domain noise data F i Data on the blank subcarrier will be converted into frequency domain noise data F. i The data at the mid-data subcarrier position is cleared to obtain new frequency domain peak-clipping data CC. i The formula is:

[0035]

[0036] In the formula, CC i (k) represents the new frequency domain peak-shaving data CC in the i-th iteration. i The (k+1)th data in the dataset, where R is the set of blank subcarrier positions. c F is the set of data subcarrier locations. i (k) represents the frequency domain noise data F during the i-th iteration. i The (k+1)th data point.

[0037] Based on time-domain peak-shaving data c i and initial peak clipping noise data f i The weighted least squares method is used to calculate the optimal iteration coefficients for the i-th iteration, as shown in the formula:

[0038]

[0039] In the formula, Let c be the preferred iteration coefficient for the i-th iteration, γ represent the set of positions where peak clipping was not performed, and c is the peak clipping value. i (n) represents the time-domain peak-shaving data of the i-th iteration. i The (n+1)th data in the array, f is the weight coefficient at the i-th iteration. i (n) represents the initial peak-shaving noise data f in the i-th iteration. i The (n+1)th data in the sequence;

[0040] Based on the optimal iteration coefficients of the i-th iteration and the time-domain peak-shaving data c i and the time-domain data y of the i-th iteration i Calculate the time-domain data y for the (i+1)th iteration. i+1 The formula is:

[0041] A PAPR suppression device, comprising:

[0042] The frequency domain data acquisition module divides the subcarriers of the radar-communication integrated system into data subcarriers and blank subcarriers to acquire frequency domain data Y. The frequency domain data Y is the radar-communication integrated frequency domain data, which includes radar data subcarriers, communication data subcarriers, and blank subcarriers. The radar data subcarriers are the data subcarriers for modulating radar data, and the communication data subcarriers are the data subcarriers for modulating communication data.

[0043] The IFFT transform module performs an IFFT transform on the frequency domain data Y to obtain the time domain data y.

[0044] The iterative peak-shaving module uses a subcarrier reservation method based on weighted least squares to iteratively smooth the time-domain data y, and then converts the iteratively smoothed time-domain data into a signal for use in the radar-communication integrated system.

[0045] A computer-readable storage medium stores one or more programs, the one or more programs including instructions that, when executed by a computing device, cause the computing device to perform a PAPR suppression method.

[0046] A computer device includes one or more processors and one or more memories, wherein one or more programs are stored in the one or more memories and configured to be executed by the one or more processors, the one or more programs including instructions for performing a PAPR suppression method.

[0047] The beneficial effects achieved by this invention are as follows:

[0048] 1. This invention divides the subcarriers of the radar-communication integrated system into data subcarriers and blank subcarriers, obtains frequency domain data containing blank subcarriers, and suppresses PAPR through an iterative peak clipping method, thus ensuring the performance of the radar-communication integrated system without changing the bit error rate of the communication signal.

[0049] 2. This invention divides the subcarriers of the radar-communication integrated system into data subcarriers and blank subcarriers. The data subcarriers are further divided into radar subcarriers and communication subcarriers. The radar signal can reduce PAPR, and it can adapt to various resource allocation strategies. It can be flexibly adjusted according to different system requirements and performance indicators to obtain the best resource allocation scheme. It can adapt to different numbers of subcarriers, channel conditions and user needs, and can be flexibly applied to systems of various scales and scenarios.

[0050] 3. This invention uses a subcarrier reservation method based on weighted least squares for iterative peak reduction, which can achieve good PAPR suppression in 1 to 3 iterations. Compared with the traditional subcarrier reservation method, it has better convergence speed and peak reduction effect. Attached Figure Description

[0051] Figure 1 The flowchart is for the PAPR suppression method;

[0052] Figure 2 The CCDF curve for PAPR suppression using radar subcarriers and OFDM communication signals;

[0053] Figure 3 This is the CCDF curve of the subcarrier reservation method of the present invention;

[0054] Figure 4 This is a comparison chart of the PAPR suppression effects of the subcarrier reservation method and the CC-TR algorithm of this invention;

[0055] Figure 5 This is a comparison chart of the PAPR suppression effects of the subcarrier reservation method and the LSA-TR algorithm in this invention;

[0056] Figure 6 The first iteration PAPR suppression effect of the subcarrier reservation method of the present invention under different threshold amplification factors is shown in the figure.

[0057] Figure 7 The first iteration PAPR suppression effect of the subcarrier reservation method of the present invention under different numbers of reserved subcarriers is shown in the figure. Detailed Implementation

[0058] The present invention will be further described below with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and should not be used to limit the scope of protection of the present invention.

[0059] like Figure 1 As shown, a PAPR suppression method includes the following steps:

[0060] Step 1: Divide the subcarriers of the radar-communication integrated system into data subcarriers and blank subcarriers to obtain frequency domain data Y; wherein, the frequency domain data Y is the radar-communication integrated frequency domain data, including radar data subcarriers, communication data subcarriers, and blank subcarriers; the radar data subcarriers are the data subcarriers for modulating radar data, and the communication data subcarriers are the data subcarriers for modulating communication data.

[0061] Step 2: Perform an IFFT transform on the frequency domain data Y to obtain the time domain data y.

[0062] Step 3: The subcarrier reservation method based on weighted least squares is used to iteratively smooth the peaks of the time-domain data y, and the time-domain data after iterative peak smoothing is converted into a signal for use in the radar-communication integrated system.

[0063] The above method divides the subcarriers of the radar-communication integrated system into data subcarriers and blank subcarriers, obtains frequency domain data containing blank subcarriers, and suppresses PAPR through an iterative peak clipping method, thus ensuring system performance and not changing the bit error rate of the communication signal.

[0064] In an integrated radar-communication system, the transmitting station transmits an OFDM symbol containing N subcarriers, and sets L subcarriers in the symbol as blank subcarriers. The frequency domain signal of the blank subcarrier is H = [0, H(1), 0, ..., H(N-1)], and the length of H is N. Each position corresponds to a subcarrier. If the (k+1)th position corresponds to a data subcarrier, then the (k+1)th element is 0. If the (k+1)th position corresponds to a blank subcarrier, then the (k+1)th element is H(k). The frequency domain signal of the data subcarrier is G = [G(0), 0, G(2), ..., 0], and the length of G is N. Each position corresponds to a subcarrier. If the (k+1)th position corresponds to a data subcarrier, then the (k+1)th element is G(k). If the (k+1)th position corresponds to a blank subcarrier, then the (k+1)th element is 0.

[0065] Let R = {i0, i1, ..., i L-1} represents the set of blank subcarrier locations, R c Let R be the complement of the universal set {0,1,…,N-1}, representing the set of data subcarrier positions. Then G and H satisfy:

[0066]

[0067]

[0068] Frequency domain data Y can be represented as:

[0069]

[0070] M1 data subcarriers are allocated to the radar signal for radar target detection; the remaining N-M1-L data subcarriers are allocated to communication data for communication transmission, with the radar subcarriers and communication subcarriers not overlapping; based on the orthogonality of the frequency domain data, the frequency domain signal G of the data subcarrier is expressed as the superposition of radar data G1 and communication data G2:

[0071] G = G1 + G2;

[0072] In the formula, G1=[s(0),0,0,…,s(n),0,0,…,s(M1-1),0,0], G2=[0,0,a(0),…,0,0,a(j),…,,0,a(N-M1-L-1),0], and the communication signal a(j) represents the (j+1)th communication data;

[0073] Wherein, radar data s(n) represents the (n+1)th spectral sample of the linear frequency modulated signal:

[0074]

[0075] In the formula, Let B be the frequency modulation slope, B be the pulse bandwidth, T be the period of the linear frequency modulated signal, and F be the frequency modulation slope. s Let M1 be the sampling frequency, satisfying M1 = F s T.

[0076] Performing an IFFT transform on the frequency domain data Y yields the time domain data y = [y(0), y(1), ..., y(N-1)], which can be expressed by the formula:

[0077]

[0078] In the formula, Y(k) is the (k+1)th data in the frequency domain data Y, and y(n) is the (n+1)th data in the time domain sequence (i.e. y) of the integrated signal after IFFT operation.

[0079] Furthermore, a subcarrier reservation method based on weighted least squares is adopted to iteratively smooth the peaks of the time-domain data y, and the time-domain data after iterative peak smoothing is converted into a signal for use in the radar-communication integrated system.

[0080] Currently, traditional subcarrier reservation methods suffer from slow iteration speed and unsatisfactory peak-shaving effects. To optimize the iterative peak-shaving effect, as an embodiment of this invention, a weighted least squares-based subcarrier reservation method is adopted. The specific process of iteratively smoothing the time-domain data y is as follows:

[0081] 1) Initialize the iteration count i = 1, and denote the time-domain data obtained in step 2 as y. i , where i represents the number of iterations.

[0082] 2) Based on the time-domain data y of the i-th iteration i Calculate the peak-shaving threshold for the i-th iteration;

[0083] The peak-shaving threshold for the i-th iteration can be calculated using the following formula:

[0084] A i =R i ·E[y i ];

[0085] In the formula, A i R is the peak-shaving threshold for the i-th iteration. i Let E[y] be the threshold amplification factor for the i-th iteration. i ] represents time-domain data y i The average amplitude.

[0086] 3) If the time-domain data y i If the peak value is less than or equal to the peak reduction threshold, then no adjustment is needed to the time-domain data y. i The processing is completed, and the iterative peak reduction ends.

[0087] If the time-domain data y i The peak value is greater than the peak reduction threshold. Based on the peak reduction threshold, the time domain data y is adjusted. i Peak clipping is performed to obtain a time-domain limited signal. Go to 4);

[0088] The formula for peak reduction processing can be expressed as:

[0089]

[0090] In the formula, The time-domain limiting signal for the i-th iteration The (n+1)th data in the array, y i (n) represents the time-domain data y for the i-th iteration. i The (n+1)th data in the dataset.

[0091] 4) Based on the time-domain data y i and time-domain limiting signal Calculate the initial peak clipping noise data f i =[f i (0),f i (1),…,f i (N-1)];

[0092] The formula for calculating the initial peak-shaving noise data can be expressed as:

[0093]

[0094] Among them, f i (n) represents the initial peak-shaving noise data f in the i-th iteration. i The (n+1)th data in the dataset.

[0095] 5) For the initial peak-shaving noise data f i Perform an FFT transformation to obtain the initial peak-shaving noise data f. i Frequency domain noise data F i =[F i (0),F i (1),…,F i (N-1)];

[0096] The formula for FFT transformation can be expressed as:

[0097]

[0098] In the formula, F i(k) represents the frequency domain noise data F during the i-th iteration. i The (k+1)th data in the dataset.

[0099] 6) Retain frequency domain noise data F i Data on the blank subcarrier will be converted into frequency domain noise data F. i The data at the mid-data subcarrier position is cleared to obtain new frequency domain peak-clipping data CC. i =[CC i (0),CC i (1),…,CC i (N-1)];

[0100] The specific formula can be expressed as:

[0101]

[0102] In the formula, CC i (k) represents the new frequency domain peak-shaving data CC in the i-th iteration. i The (k+1)th data in the dataset.

[0103] 7) Crop clipping of new frequency domain data CC i Perform IFFT transformation to obtain time-domain peak-shaving data c i =[c i (0),c i (1),…,c i (N-1)].

[0104] 8) Based on the time-domain peak-shaving data c i and initial peak clipping noise data f i The weighted least squares method is used to calculate the optimal iteration coefficients for the i-th iteration;

[0105] The optimal iteration coefficients for the i-th iteration can be calculated using the following formula:

[0106]

[0107] In the formula, Let γ be the preferred iteration coefficient for the i-th iteration, and γ = {n||f i (n)|≠0} represents the set of positions where peak clipping was not performed (2), c i (n) represents the time-domain peak-shaving data of the i-th iteration. i The (n+1)th data in the array, is the weight coefficient at the i-th iteration.

[0108] 9) Based on the optimal iteration coefficients of the i-th iteration and the time-domain peak-shaving data c i and the time-domain data y of the i-th iteration i Calculate the time-domain data y for the (i+1)th iteration.i+1 The formula is:

[0109] 10) If i is less than the preset maximum iteration count iter, increment the iteration count by 1, i.e., i = i + 1; set y i+1 Return the time-domain sequence of the integrated signal for the next iteration; otherwise, the iteration stops when i equals the maximum number of iterations iter.

[0110] This invention employs a subcarrier reservation method based on weighted least squares for iterative peak reduction, which can achieve good PAPR suppression in 1 to 3 iterations. Compared with the traditional subcarrier reservation method, it has better convergence speed and peak reduction effect.

[0111] This invention divides the subcarriers of an integrated radar and communication system into data subcarriers and blank subcarriers. The data subcarriers are further divided into radar subcarriers and communication subcarriers. By utilizing radar signals, the PAPR (Programmable Aspect Ratio) can be reduced. At the same time, it can adapt to various resource allocation strategies and can be flexibly adjusted according to different system requirements and performance indicators to obtain the optimal resource allocation scheme. It can adapt to different numbers of subcarriers, channel conditions, and user needs, and can be flexibly applied to systems of various sizes and scenarios.

[0112] To verify the above method, the following simulation experiment was conducted:

[0113] The radar-communication integrated system transmits 1000 pulses, each pulse containing a complete OFDM symbol. Each symbol contains 256 subcarriers, with the first 240 being data subcarriers. The first 128 subcarriers modulate radar data, the next 112 subcarriers modulate 16QAM data, and the last 16 blank subcarriers are reserved for peak-clipping data. For different iteration numbers i, let R... i =1.2, then the threshold A i =1.2E[y i The remaining simulation data are shown in Table 1.

[0114] Table 1 Simulation Data

[0115] radar carrier frequency 1.5GHz signal bandwidth 1MHz Signal bandwidth 64μs Sampling frequency 2MHz Pulse period 480μs Signal-to-noise ratio 20dB Number of iterations 5

[0116] Experiment content:

[0117] (1) For the experimental scenario, PAPR suppression was compared using radar subcarriers and OFDM communication signals, and CCDF curves were plotted, such as... Figure 2 As shown. Figure 2 This indicates that the use of radar subcarriers in this invention can effectively reduce the PAPR of the algorithm. The more radar subcarriers there are, the more obvious the PAPR suppression becomes.

[0118] (2) For the experimental scenario, the subcarrier reservation method of this invention is used to suppress PAPR of the integrated signal, and the CCDF curve is plotted, as shown below. Figure 3 As shown. Figure 3 This indicates that the proposed PAPR suppression algorithm can achieve good PAPR suppression results within a limited number of iterations, and the algorithm converges very quickly.

[0119] (3) For the experimental scenario, the PAPR suppression effect of the subcarrier reservation method of this invention will be compared with that of the CC-TR algorithm, and the CCDF curve will be plotted, as shown below. Figure 4 As shown. Figure 4 This indicates that, compared to the CC-TR algorithm, the PAPR suppression algorithm has a better convergence speed and a better suppression effect.

[0120] (4) For the experimental scenario, the PAPR suppression effect of the subcarrier reservation method of this invention will be compared with that of the LSA-TR algorithm, and CCDF curves will be plotted, as shown below. Figure 5 As shown. From Figure 5 It can be seen that the final suppression effects of the two algorithms are similar, but the PAPR suppression algorithm has fewer iterations and lower computational complexity.

[0121] (5) For the experimental scenario, the threshold amplification factor was successively set to 0.8, 0.9, 1, 1.1, 1.2, 1.3, and 1.4, while other parameters remained unchanged. The subcarrier reservation method of this invention was used to suppress PAPR of the integrated signal, and the CCDF curve was plotted, as shown below. Figure 6 As shown, starting from 0.8, the PAPR suppression effect improves with increasing amplitude amplification factor after the first iteration. The optimal PAPR suppression effect is achieved when R = 1.2. However, as the coefficient R increases... i As the amplitude increases, the suppression effect of PAPR deteriorates. Overall, the optimal amplitude amplification factor under these parameters is R. i =1.2.

[0122] (6) For the experimental scenario, the number of reserved subcarriers is set to 8, 12, 16, 20, 24, 28, 32, and 36, respectively, while other parameters remain unchanged. The subcarrier reservation method of this invention is used to suppress PAPR of the integrated signal, and the CCDF curve is plotted, as shown below. Figure 7 As shown, the PAPR suppression effect of this algorithm improves with the increase in the number of reserved blank subcarriers. However, with the increase in the number of reserved subcarriers, the peak clipping data not only fails to clip the peak signal, but the PAPR suppression effect also slightly reverses. Overall, the optimal number of reserved subcarriers under these parameters is 12 or 16.

[0123] Based on the same technical solution, the present invention also discloses a virtual device for the above method, a PAPR suppression device, comprising:

[0124] The frequency domain data acquisition module divides the subcarriers of the radar-communication integrated system into data subcarriers and blank subcarriers to acquire frequency domain data Y. The frequency domain data Y is the radar-communication integrated frequency domain data, including radar data subcarriers, communication data subcarriers, and blank subcarriers. The radar data subcarriers are the data subcarriers that modulate radar data, and the communication data subcarriers are the data subcarriers that modulate communication data.

[0125] The IFFT transform module performs an IFFT transform on the frequency domain data Y to obtain the time domain data y.

[0126] The iterative peak-shaving module uses a subcarrier reservation method based on weighted least squares to iteratively smooth the time-domain data y, and then converts the iteratively smoothed time-domain data into a signal for use in the radar-communication integrated system.

[0127] The data processing flow and methods of each module of the above device are consistent, and will not be described again here.

[0128] Based on the same technical solution, the present invention also discloses a computer-readable storage medium that stores one or more programs, the one or more programs including instructions that, when executed by a computing device, cause the computing device to perform a PAPR suppression method.

[0129] Based on the same technical solution, the present invention also discloses a computer device, including one or more processors and one or more memories, wherein one or more programs are stored in the one or more memories and configured to be executed by the one or more processors, and the one or more programs include instructions for performing a PAPR suppression method.

[0130] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0131] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0132] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0133] These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable apparatus for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0134] The above are merely embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention are included within the scope of the claims of the present invention pending approval.

Claims

1. A PAPR suppression method, characterized in that, include: The subcarriers of the radar-communication integrated system are divided into data subcarriers and blank subcarriers to obtain frequency domain data Y. The frequency domain data Y is the radar-communication integrated frequency domain data, which includes radar data subcarriers, communication data subcarriers, and blank subcarriers. The radar data subcarriers are the data subcarriers that modulate radar data, and the communication data subcarriers are the data subcarriers that modulate communication data. Perform an IFFT transform on the frequency domain data Y to obtain the time domain data y; A subcarrier reservation method based on weighted least squares is used to iteratively smooth the peaks of the time-domain data y, and the time-domain data after iterative peak smoothing is converted into a signal for use in the radar-communication integrated system. Each iteration of peak reduction includes: 1) Based on the time-domain data y of the i-th iteration i Calculate the peak-shaving threshold for the i-th iteration; 2) If the time-domain data y i If the peak value is less than or equal to the peak reduction threshold, then no adjustment is needed to the time-domain data y. i Processing is performed, and the iterative peak reduction ends; If the time-domain data y i The peak value is greater than the peak reduction threshold. Based on the peak reduction threshold, the time domain data y is adjusted. i Peak clipping is performed to obtain a time-domain limited signal. (Go to 3) 3) Based on the time-domain data y i and time-domain limiting signal Calculate the initial peak-shaving noise data f i ; 4) For the initial peak-shaving noise data f i Perform an FFT transformation to obtain the initial peak-shaving noise data f. i Frequency domain noise data F i ; 5) Retain frequency domain noise data F i Data on the blank subcarrier will be converted into frequency domain noise data F. i The data at the mid-data subcarrier position is cleared to obtain new frequency domain peak-clipping data CC. i ; 6) Crop clipping of new frequency domain data CC i Perform IFFT transformation to obtain time-domain peak-shaving data c i ; 7) Based on time-domain peak-shaving data c i and initial peak clipping noise data f i The weighted least squares method is used to calculate the optimal iteration coefficients for the i-th iteration, as shown in the formula: ； In the formula, Let be the preferred iteration coefficient for the i-th iteration. This represents the set of locations where peak clipping was not performed. For the time-domain peak-shaving data c in the i-th iteration i The (n+1)th data in the array, The weight coefficients are for the i-th iteration. The initial peak-shaving noise data f for the i-th iteration i The (n+1)th data in the sequence; 8) Based on the optimal iteration coefficients of the i-th iteration and the time-domain peak-shaving data c i and the time-domain data y of the i-th iteration i Calculate the time-domain data y for the (i+1)th iteration. i+1 The formula is: .

2. The PAPR suppression method according to claim 1, characterized in that, The formula for frequency domain data Y is: ； In the formula, G is the frequency domain signal of the data subcarrier, the length of G is N, each position corresponds to a subcarrier, if the (k+1)th position corresponds to a data subcarrier, then the (k+1)th element is G(k), if the (k+1)th position corresponds to a blank subcarrier, then the (k+1)th element is 0; G = G1 + G2, G1 is radar data, G2 is communication data; H is the frequency domain signal of the blank subcarrier. The length of H is N. Each position corresponds to a subcarrier. If the (k+1)th position corresponds to a data subcarrier, then the (k+1)th element is 0. If the (k+1)th position corresponds to a blank subcarrier, then the (k+1)th element is H(k).

3. The PAPR suppression method according to claim 1, characterized in that, Based on the time-domain data y of the i-th iteration i The peak-shaving threshold for the i-th iteration is calculated using the following formula: ； In the formula, R is the peak-shaving threshold for the i-th iteration. i Let be the threshold amplification factor for the i-th iteration. For time-domain data y i The average amplitude.

4. The PAPR suppression method according to claim 1, characterized in that, Based on the peak reduction threshold, the time-domain data y i Peak clipping is performed to obtain a time-domain limited signal. The formula is: ； In the formula, The time-domain limiting signal for the i-th iteration The (n+1)th data in the array, For the time-domain data y in the i-th iteration i The (n+1)th data in the sequence; Based on time-domain data y i and time-domain limiting signal Calculate the initial peak-shaving noise data f i The formula is: ； in, The initial peak-shaving noise data f for the i-th iteration i The (n+1)th data in the dataset.

5. The PAPR suppression method according to claim 1, characterized in that, Preserve frequency domain noise data F i Data on the blank subcarrier will be converted into frequency domain noise data F. i The data at the mid-data subcarrier position is cleared to obtain new frequency domain peak-clipping data CC. i The formula is: ； In the formula, CC i (k) represents the new frequency domain peak-shaving data CC in the i-th iteration. i The (k+1)th data in the dataset, where R is the set of blank subcarrier positions. c F is the set of data subcarrier locations. i (k) represents the frequency domain noise data F during the i-th iteration. i The (k+1)th data point.

6. A PAPR suppression device, characterized in that, include: The frequency domain data acquisition module divides the subcarriers of the radar-communication integrated system into data subcarriers and blank subcarriers to acquire frequency domain data Y. The frequency domain data Y is the radar-communication integrated frequency domain data, which includes radar data subcarriers, communication data subcarriers, and blank subcarriers. The radar data subcarriers are the data subcarriers for modulating radar data, and the communication data subcarriers are the data subcarriers for modulating communication data. The IFFT transform module performs an IFFT transform on the frequency domain data Y to obtain the time domain data y. The iterative peak-shaving module employs a subcarrier reservation method based on weighted least squares to iteratively smooth the time-domain data y, converting the iteratively smoothed time-domain data into a signal for use in the integrated radar-communication system. Each iteration of peak-shaving includes: 1) Based on the time-domain data y of the i-th iteration i Calculate the peak-shaving threshold for the i-th iteration; 2) If the time-domain data y i If the peak value is less than or equal to the peak reduction threshold, then no adjustment is needed to the time-domain data y. i Processing is performed, and the iterative peak reduction ends; If the time-domain data y i The peak value is greater than the peak reduction threshold. Based on the peak reduction threshold, the time domain data y is adjusted. i Peak clipping is performed to obtain a time-domain limited signal. (Go to 3) 3) Based on the time-domain data y i and time-domain limiting signal Calculate the initial peak-shaving noise data f i ; 4) For the initial peak-shaving noise data f i Perform an FFT transformation to obtain the initial peak-shaving noise data f. i Frequency domain noise data F i ; 5) Retain frequency domain noise data F i Data on the blank subcarrier will be converted into frequency domain noise data F. i The data at the mid-data subcarrier position is cleared to obtain new frequency domain peak-clipping data CC. i ; 6) Crop clipping of new frequency domain data CC i Perform IFFT transformation to obtain time-domain peak-shaving data c i ; 7) Based on time-domain peak-shaving data c i and initial peak clipping noise data f i The weighted least squares method is used to calculate the optimal iteration coefficients for the i-th iteration, as shown in the formula: ； In the formula, Let be the preferred iteration coefficient for the i-th iteration. This represents the set of locations where peak clipping was not performed. For the time-domain peak-shaving data c in the i-th iteration i The (n+1)th data in the array, The weight coefficients are for the i-th iteration. The initial peak-shaving noise data f for the i-th iteration i The (n+1)th data in the sequence; 8) Based on the optimal iteration coefficients of the i-th iteration and the time-domain peak-shaving data c i and the time-domain data y of the i-th iteration i Calculate the time-domain data y for the (i+1)th iteration. i+1 The formula is: .

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores one or more programs, the one or more programs including instructions that, when executed by a computing device, cause the computing device to perform any of the methods described in claims 1 to 5.

8. A computer device, characterized in that, include: One or more processors and one or more memories, one or more programs stored in the one or more memories and configured to be executed by the one or more processors, the one or more programs including instructions for performing any of the methods of claims 1 to 5.

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