CN112968856B - PTS peak-to-average ratio optimization method and signal processing system based on frequency domain preprocessing - Google Patents

Abstract

The invention relates to a PTS peak-to-average ratio optimization method based on frequency domain preprocessing, which belongs to the technical field of wireless communication power amplifier efficiency optimization, and solves the problem that the existing PTS-based PAPR suppression method has too much calculation and the power optimization capability is limited. The method comprises: performing frequency domain conversion on the input M-QAM signal, and performing signal segmentation on the OFDM frequency domain signal obtained by the frequency domain conversion; inputting each divided OFDM frequency domain sub-signal into a preset frequency domain scrambling model in turn to obtain discrete OFDM results after multiple PTS multiplicative scrambling corresponding to the OFDM frequency domain signal; inputting the discrete OFDM results after each PTS multiplicative scrambling into a preset Spacing evaluation model to obtain a corresponding OFDM signal dispersion estimate; The discrete OFDM result corresponding to the minimum estimated value of DM signal dispersion is subjected to IFFT transformation to obtain the time-domain transmission signal after peak-to-average ratio suppression. The calculation complexity is reduced, and the peak-to-average ratio suppression of the input signal is performed quickly and effectively.

Description

PTS peak-to-average ratio optimization method and signal processing system based on frequency domain preprocessing

technical field

The invention relates to the technical field of wireless communication power amplifier efficiency optimization, in particular to a PTS peak-to-average ratio optimization method based on frequency domain preprocessing and a signal processing system.

Background technique

With the development of various key technologies such as ultra-dense network (UDN), massive MIMO, and millimeter wave communication, 5G networks have achieved a 1,000-fold increase in network capacity and a large connection target of at least 100 billion devices, while leading to an intensified energy crisis. The cost of energy consumption has gradually eroded the profitability of the network. Most of the energy consumption in the communication process occurs on the side of the wireless base station. The low efficiency of the power amplifier causes most of the energy consumption to be wasted in the form of heat, which deteriorates the environment of the computer room.

The 5G system uses an Orthogonal Frequency Division Multiplexing (OFDM) system. The OFDM signal is composed of multiple sub-carriers during transmission. Due to the close phase of adjacent sub-carriers, the peak value of the sub-carriers may be superimposed, resulting in a peak-to-average ratio, which makes the power amplifier unable to work in the linear region, resulting in a reduction in the working efficiency of the power amplifier and unnecessary energy consumption.

The PAPR suppression method based on partial transmission sequence (PTS) can improve the working efficiency of 5G system. However, in the prior art, the PAPR suppression method is a linear optimization process, and the space for the number of groups, a large number of IFFT transformations, and complex PAPR time-domain evaluation will all cause a sudden increase in the amount of calculation in the system, which in turn constrains the computing power of the entire system, resulting in limited system efficiency optimization performance.

Contents of the invention

In view of the above analysis, the embodiment of the present invention aims to provide a PTS peak-to-average ratio optimization method and a signal processing system based on frequency domain preprocessing, to solve the problem that the existing PTS-based PAPR suppression method has too much calculation and the power optimization capability is limited.

On the one hand, the embodiment of the present invention provides a PTS peak-to-average ratio optimization method based on frequency domain preprocessing, including the following steps:

Perform frequency domain conversion on the input M-QAM signal, and perform signal segmentation on the OFDM frequency domain signal obtained by frequency domain conversion;

Input each divided OFDM frequency domain sub-signal into the preset frequency domain scrambling model in turn to obtain the discrete OFDM results after multiple PTS multiplicative scrambling corresponding to the OFDM frequency domain signal;

Input the discrete OFDM result after multiplicative scrambling of each PTS into the preset Spacing evaluation model to obtain the corresponding OFDM signal dispersion estimate;

Search for the discrete OFDM result corresponding to the minimum estimated value of the OFDM signal dispersion, perform IFFT transformation, and obtain the time-domain transmission signal after peak-to-average ratio suppression.

The beneficial effects of the above technical solution are as follows: Aiming at the defect of high computational complexity of the existing PTS-based PAPR suppression method, a low-complexity PTS peak-to-average ratio optimization method based on frequency domain preprocessing is proposed, which can effectively suppress the signal peak-to-average ratio. Through the combined method of preprocessing (frequency domain scrambling) and frequency domain evaluation (preset Spacing evaluation model), V-1 IFFT transformations are avoided, and the complexity of PTS is reduced to about 1/V. Through the Spacing evaluation model with low peak-to-average ratio probability, an excellent scrambled signal can be pre-selected before IFFT as a transmission signal. Under low complexity conditions, while maintaining a good peak-to-average ratio suppression performance.

Based on a further improvement of the above method, the step of performing frequency domain conversion on the input M-QAM signal includes:

Perform OFDM frequency domain framing on the input M-QAM signal to obtain the OFDM frequency domain signal corresponding to the M-QAM signal

X＝[X ₁ ,…,X _i ,…,X _N ]

In the formula, Xi _is the ith subcarrier of the OFDM frequency domain signal, and N represents the number of subcarriers of the OFDM frequency domain signal.

The beneficial effect of the above further improvement scheme is that frequency domain OFDM planning and signal carrier allocation are carried out, which can effectively improve spectrum efficiency, resist frequency selective fading in the transmission process, and have high anti-interference ability.

Further, the step of performing signal segmentation on the OFDM frequency domain signal obtained by frequency domain conversion includes:

By random partitioning method, the OFDM frequency domain signal is divided into mutually disjoint sub-blocks, and each sub-block is regarded as an OFDM frequency domain sub-signal X _v

In the formula, V represents the total number of divided sub-blocks, and the subscript v represents the order of sub-blocks, v∈{1,2,…,V}.

The beneficial effect of the above further improvement scheme is that dividing the OFDM frequency domain signal into sub-blocks can improve the degree of freedom of scrambling, a higher total number of blocks V can obtain a higher degree of constellation dispersion, and can effectively reduce the probability of peak generation, and sub-block division can achieve an effective compromise between PTS complexity and peak-to-average ratio suppression performance.

Further, the preset frequency domain scrambling model is

In the formula, Q _iv is the item v element in row i of the full space Q of the multiplicative scrambling code sequence.

The beneficial effect of the above-mentioned further improvement scheme is that: the above-mentioned frequency-domain scrambling model is a multiplicative scrambling method, which can optimize signal dispersion, and corresponding multiplicative descrambling can be completed at the receiving end. The peak-to-average ratio can be effectively reduced under the condition of transmission without loss of signal quality.

Further, inputting each divided OFDM frequency-domain sub-signal into a preset frequency-domain scrambling model in sequence to obtain discrete OFDM results after multiple PTS multiplicative scrambling corresponding to the OFDM frequency-domain signal, further comprising:

The rotation phase factor b _v corresponding to each OFDM frequency domain sub-signal X _v is obtained by the following formula

b _v ＝e ^j2πi/V |i＝1,...,V

In the formula, | is a conditional operator;

According to the above rotation phase factor b _v , perform the permutation and combination in the following formula to obtain the full space Q of the multiplicative scrambling code sequence in the frequency domain scrambling model

V! ＝V·(V-1)...1

Input all OFDM frequency domain sub-signals X _v into the preset frequency domain scrambling model in sequence to obtain V corresponding to the OFDM frequency domain signal! Discrete OFDM results after PTS multiplicative scrambling

The beneficial effect of the above further improvement scheme is: to generate the full space Q of the scrambling code sequence, and complete the scrambling in the frequency domain, compared with the existing PTS random sampling scrambling space, it is easier and faster to obtain the optimal solution, and obtain better peak-to-average ratio suppression effect.

Further, the Spacing evaluation model is

In the formula, S is the estimated value of OFDM signal dispersion, for /> The kth frequency domain signal in , /> for /> mean value.

The beneficial effect of the above-mentioned further improvement scheme is: the evaluation of Spacing frequency-domain dispersion through the above-mentioned Spacing evaluation model can predict a low peak-to-average ratio signal with a high probability, and obtain an excellent PTS peak-to-average ratio suppression scrambling signal more easily with lower complexity.

On the other hand, an embodiment of the present invention provides a signal processing system based on frequency domain preprocessing, including sequentially connected:

The preprocessing module is used to perform frequency domain conversion on the input M-QAM signal, perform signal segmentation on the OFDM frequency domain signal obtained by frequency domain conversion, and transmit each divided OFDM frequency domain sub-signal to the signal generation and screening module;

The signal generation and screening module is used to sequentially input each OFDM frequency domain sub-signal into a preset frequency domain scrambling model to obtain discrete OFDM results after multiple PTS multiplicative scrambling corresponding to the OFDM frequency domain signal; and input the discrete OFDM results after each PTS multiplicative scrambling into a preset Spacing evaluation model to obtain a corresponding OFDM signal dispersion estimated value; select the discrete OFDM result corresponding to the minimum value of the OFDM signal dispersion estimated value and transmit it to the output module;

The output module is used to perform IFFT transformation on the received discrete OFDM result to obtain the time-domain transmission signal after peak-to-average ratio suppression.

The beneficial effects of the above technical solution are as follows: the complexity of the existing PTS-based PAPR suppression method mainly focuses on IFFT transformation and time-domain PTS scrambling to optimize OFDM signals. The above technical solution predicts the PTS scrambling code and selects the OFDM signal through the Spacing evaluation model in the frequency domain (that is, the discrete OFDM result corresponding to the minimum value of the OFDM signal dispersion estimate), which can avoid the complexity of the IFFT transformation, and select the low peak-to-average ratio scrambled signal from the whole space with a very small cost and time delay, while maintaining a good peak-to-average ratio suppression performance.

Based on the further improvement of the above system, the preprocessing module executes the following procedures:

Perform OFDM frequency domain framing on the input M-QAM signal to obtain the OFDM frequency domain signal corresponding to the M-QAM signal

X＝[X ₁ ,…,X _i ,…,X _N ]

In the formula, Xi _is the ith subcarrier of the OFDM frequency domain signal, and N represents the number of subcarriers of the OFDM frequency domain signal;

The OFDM frequency domain signal is divided into mutually disjoint sub-blocks by a random segmentation method, and each sub-block is used as an OFDM frequency domain sub-signal

In the formula, V represents the total number of divided sub-blocks, subscript v represents the order of sub-blocks, v∈{1,2,…,V};

Each divided OFDM frequency domain sub-signal is sequentially transmitted to the signal generation and screening module.

The beneficial effect of adopting the above-mentioned further improvement scheme is: increasing the degree of freedom of optimization from the frequency domain dimension, allowing more constellation points to complete multiplicative optimization, and obtaining an improvement in peak-to-average ratio suppression performance.

Further, the signal generation and screening module performs the following procedures to obtain discrete OFDM results after multiple PTS multiplicative scrambling corresponding to the OFDM frequency domain signal:

The rotation phase factor b _v corresponding to each OFDM frequency domain sub-signal X _v is obtained by the following formula

b _v ＝e ^j2πi/V |i＝1,...,V

In the formula, | is a conditional operator;

According to the above rotation phase factor b _v , perform the permutation and combination in the following formula to obtain the full space Q of the multiplicative scrambling code sequence in the frequency domain scrambling model

Input all OFDM frequency domain sub-signals X _v into the preset frequency domain scrambling model in the following formula in sequence to obtain the V corresponding to the OFDM frequency domain signal! Discrete OFDM results after PTS multiplicative scrambling

In the formula, Q _iv is the item v element in row i of the full space Q of the multiplicative scrambling code sequence.

The beneficial effects of adopting the above-mentioned further improvement scheme are: increasing the degree of freedom of optimization from the space dimension, allowing constellation points to be multiplicatively discrete in a larger constellation space, generating OFDM frequency-domain discrete signals scrambled in the full spatial frequency domain, avoiding the complexity of IFFT transformation, and obtaining all candidate OFDM signals of PTS (that is, the discrete OFDM result after PTS multiplicative scrambling) with less complexity ), it is easier to contain the optimal solution.

Further, the signal generation and screening module executes the following procedure to obtain the estimated value of OFDM signal dispersion:

Input the discrete OFDM result after multiplicative scrambling of each PTS into the Spacing evaluation model of the following formula to obtain the corresponding OFDM signal dispersion estimate S

where, is the estimated value of OFDM signal dispersion, for /> The kth frequency domain signal in , /> for /> mean value.

The beneficial effect of adopting the above-mentioned further improvement scheme is: the Spacing evaluation is performed from the PTS candidate OFDM frequency domain signals in the whole space, and the OFDM signal with low peak-to-average ratio is quickly converged as the transmission signal. Using the above-mentioned Spacing evaluation model to evaluate the frequency-domain dispersion of Spacing can predict low peak-to-average ratio signals with a high probability, and obtain excellent PTS peak-to-average ratio suppression scrambling signals more easily with lower complexity.

In the present invention, the above technical solutions can also be combined with each other to realize more preferred combination solutions. Additional features and advantages of the invention will be set forth in the description which follows, and some of the advantages will be apparent from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the matter particularly pointed out in the written description and appended drawings.

Description of drawings

The drawings are for the purpose of illustrating specific embodiments only and are not to be considered as limitations of the invention, and like reference numerals refer to like parts throughout the drawings.

1 is a schematic diagram of the steps of the PTS peak-to-average ratio optimization method based on frequency domain preprocessing in Embodiment 1 of the present invention;

2 is a schematic diagram of the principle of the PTS peak-to-average ratio optimization method based on frequency domain preprocessing in Embodiment 2 of the present invention;

FIG. 3 is a schematic diagram of peak-to-average ratio suppression performance evaluation of the PTS peak-to-average ratio optimization method based on frequency-domain preprocessing in Embodiment 2 of the present invention;

FIG. 4 is a schematic diagram of composition of a signal processing system based on frequency domain preprocessing according to Embodiment 3 of the present invention.

Detailed ways

Preferred embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings, wherein the accompanying drawings constitute a part of the application and together with the embodiments of the present invention are used to explain the principle of the present invention and are not intended to limit the scope of the present invention.

Example 1

A specific embodiment of the present invention discloses a PTS peak-to-average ratio optimization method based on frequency domain preprocessing, as shown in Figure 1, including the following steps:

S1. Perform frequency domain conversion on the input M-QAM signal, and perform signal segmentation on the OFDM frequency domain signal obtained by the frequency domain conversion;

S2. Input each of the divided OFDM frequency domain sub-signals into a preset frequency domain scrambling model in turn to obtain discrete OFDM results after multiple PTS multiplicative scrambling corresponding to the OFDM frequency domain signal;

S3. Input the discrete OFDM result after multiplicative scrambling of each PTS into the preset Spacing evaluation model to obtain the corresponding OFDM signal dispersion estimation value;

S4. Search for the discrete OFDM result corresponding to the minimum estimated value of the OFDM signal dispersion, perform IFFT transformation, and obtain the time-domain transmission signal after peak-to-average ratio suppression.

Compared with the prior art, the method provided in this embodiment combines preprocessing (frequency domain scrambling) and frequency domain evaluation (preset Spacing evaluation model), that is, performs frequency domain dispersion Spacing evaluation before time domain IFFT, predicts an excellent PAPR suppression OFDM signal, avoids V-1 IFFT transformations, reduces the complexity of PTS to about 1/V of the prior art, and maintains an excellent PAPR suppression effect. Domain optimization Spacing-PTS algorithm. Under the condition of low complexity, it maintains good peak-to-average ratio suppression performance.

Example 2

Optimizing on the basis of Embodiment 1, step S1 is further refined as:

S11. Perform OFDM frequency domain framing on the input M-QAM signal to obtain the OFDM frequency domain signal corresponding to the M-QAM signal

X＝[X ₁ ,…,X _i ,…,X _N ] (1)

In the formula, Xi _is the ith subcarrier of the OFDM frequency domain signal, and N represents the number of subcarriers of the OFDM frequency domain signal.

S12. By a random segmentation method, the OFDM frequency domain signal is divided into V groups of disjoint sub-blocks, and each sub-block is used as an OFDM frequency domain sub-signal X _v to construct an OFDM frequency domain signal X

In the formula, V represents the total number of divided sub-blocks, and the subscript v represents the order of sub-blocks, v∈{1,2,…,V}.

In order for each sub-block not to interfere with other sub-blocks during multiplicative scrambling and to ensure signal quality, preferably, the sub-blocks are equal in size and orthogonal to each other, and elements in each sub-block do not interfere with each other.

Preferably, step S2 is further refined as:

S21. Obtain the rotation phase factor b _v corresponding to each OFDM frequency domain sub-signal X _v by the following formula, and assign different rotation phase factors to each sub-block

b _v ＝e ^j2πi/V |i＝1,...,V (3)

In the formula, | is a conditional operator.

S22. Perform the permutation and combination in the following formula according to the above rotation phase factor b _v to obtain the full space Q of the multiplicative scrambling code sequence in the frequency domain scrambling model

Exemplarily, when V=3

S23. Input all OFDM frequency-domain sub-signals X _v into the preset frequency-domain scrambling model in the following formula in sequence to obtain V corresponding to the OFDM frequency-domain signal! Discrete OFDM results after PTS multiplicative scrambling

In the formula, Q _iv is the item v element in row i of the full space Q of the multiplicative scrambling code sequence.

Preferably, the Spacing evaluation model in step S3 is

In the formula, S is the estimated value of OFDM signal dispersion, for /> The kth frequency domain signal in , /> for /> mean value.

As a discrete center point, the smaller the S value, the higher the dispersion; the peak-to-average ratio is mainly generated by the superposition of similar phase multi-carriers, and the signal with a higher dispersion has a smaller probability of producing a peak-to-average ratio. Although the theoretical optimal solution cannot be obtained directly, it can be used as an effective suboptimal peak-to-average ratio optimization scheme.

It should be noted that step S3 is for the above V! A discrete OFDM result Dispersion evaluation based on the Spacing evaluation model, from V! Group Discrete OFDM Results /> Select the discrete OFDM result of the smallest Spacing match.

Step S4 directly performs IFFT transformation on the discrete OFDM result corresponding to the minimum value of the dispersion estimated value to obtain the time-domain transmission signal after peak-to-average ratio suppression.

Compared with the prior art, the beneficial effects of the method in this embodiment are as follows.

The existing PTS-based PAPR suppression method (hereinafter referred to as PTS, the principle shown in Figure 2) is mainly constrained by computational complexity, and it is difficult to obtain a better PAPR suppression effect. The compromise between PAPR suppression performance and implementation complexity has always been a difficult problem in industry and academia. Computational complexity can be understood as the quantifiable resources that a computer needs to consume to calculate an algorithm. The more computing resources that need to be consumed, the greater the delay requirement will be. Considering comprehensively, the computational complexity of the complex multiplier required by the existing PTS is expressed as:

g ₁ =V(LN/2)·log ₂ LN (7)

The computational complexity of the required real adder is:

g ₂ ＝VLNlog ₂ LN+(V-1)LN (8)

Through the analysis of the existing PTS, the computational complexity is mainly concentrated in: m times of search calculation with random selection of phase combinations, and V groups of IFFT transformations. Among them, the computational complexity of group V IFFT accounts for the vast majority, and even the calculation overhead of m searches can be ignored.

The principle of the Spacing-PTS improvement method proposed in this embodiment is shown in Figure 2, which avoids the calculation overhead of the V-1 group IFFT, and finally only generates a group of N-IFFT time domain signals; frequency domain scrambling and V! The calculation amount of the group space Spacing evaluation is also much smaller than the calculation amount of a group IFFT. As shown in Table 1, the computational complexity of the existing PTS and the computational complexity of the Spacing-PTS in this embodiment are compared.

Table 1 Comparative analysis of the computational complexity of the existing PTS technology and the improved Spacing-PTS in the frequency domain of this embodiment

Considering comprehensive quantification, the complexity of existing PTS is concentrated in the multiplier, and the calculation complexity of Spacing-PTS in this embodiment is only 1/V of the traditional calculation amount. Through the analysis of test results below, the existing PTS is compared with the Spacing-PTS performance of this embodiment: first, the number of carriers in the OFDM signal is set to N=1024, the number of upsampling in the OFDM system is L=4, and the number of subcarriers in the PTS technology is V=6, and the existing PTS and the Spacing-PTS of this embodiment are experimentally simulated by the method of random division, as shown in Figure 3. At CCDF=10 ^-3 , the PAPR performance of the Spacing-PTS in this embodiment is similar to that of the existing PTS algorithm when the preselected space m=32, and only 0.2dB worse than the performance at the theoretical extreme value PTS m=720. Wherein, m=32 is an acceptable general selection threshold of actual search implementation complexity and time delay of the existing PTS. The Spacing-PTS in this embodiment has an implementation complexity of only about 1/V, about 5.67%, on the premise of maintaining the peak-to-average ratio suppression performance of the existing PTS.

Compared with Embodiment 1, the method provided by this embodiment expands the degrees of freedom of scrambling from the frequency domain and the spatial domain respectively, and generates all candidate signals with a very small complexity under the full space condition, and conducts Spacing evaluation from the perspective of the frequency domain, predicts and accelerates convergence and pre-selects an excellent peak-to-average ratio suppression signal, all implemented in the frequency domain, effectively avoiding the main complexity of the IFFT transformation.

Example 3

The present invention also provides a signal processing system corresponding to the method described in Embodiment 1 or 2, including a preprocessing module, a signal generating and filtering module, and an output module connected in sequence, as shown in FIG. 4 .

The preprocessing module is used to perform frequency domain conversion on the input M-QAM signal, perform signal segmentation on the OFDM frequency domain signal obtained by frequency domain conversion, and transmit each divided OFDM frequency domain sub-signal to the signal generation and screening module.

The signal generation and screening module is used to sequentially input each OFDM frequency domain sub-signal into a preset frequency domain scrambling model to obtain discrete OFDM results after multiple PTS multiplicative scrambling corresponding to the OFDM frequency domain signal; and input the discrete OFDM results after each PTS multiplicative scrambling into a preset Spacing evaluation model to obtain a corresponding OFDM signal dispersion estimate value; select the discrete OFDM result corresponding to the minimum value of the OFDM signal dispersion estimate value and transmit it to the output module.

The output module is used to perform IFFT transformation on the received discrete OFDM result to obtain the time-domain transmission signal after peak-to-average ratio suppression.

Preferably, the preprocessing module executes the following procedures:

SS1. Perform OFDM frequency domain conversion (frequency domain framing) on the input M-QAM signal, and establish the OFDM frequency domain signal corresponding to the M-QAM signal by the following formula

X＝[X ₁ ,…,X _N ] (9)

In the formula, X _N represents the Nth subcarrier of the OFDM frequency domain signal, and N represents the number of subcarriers of the OFDM frequency domain signal;

SS2. By random segmentation method, the OFDM frequency domain signal is divided into mutually disjoint sub-blocks, and each sub-block is used as an OFDM frequency domain sub-signal

In the formula, V represents the total number of divided sub-blocks, subscript v represents the order of sub-blocks, v∈{1,2,…,V};

SS3. Transmit each of the divided OFDM frequency domain sub-signals to the signal generation and screening module in sequence.

Preferably, the signal generation and screening module executes the following procedures:

SS4. Obtain the rotation phase factor b _v corresponding to each OFDM frequency domain sub-signal X _v by the following formula

b _v ＝e ^j2πi/V |i＝1,...,V (11)

In the formula, | is a conditional operator.

SS5. Perform the permutation and combination in the following formula according to the above rotation phase factor b _v to obtain the full space Q of the multiplicative scrambling code sequence in the frequency domain scrambling model

SS6. Input all OFDM frequency domain sub-signals X _v into the preset frequency domain scrambling model in the following formula in sequence to obtain the V corresponding to the OFDM frequency domain signal! Discrete OFDM results after PTS multiplicative scrambling

In the formula, Q _iv is the item v element in row i of the full space Q of the multiplicative scrambling code sequence.

SS7. Input the discrete OFDM result after multiplicative scrambling of each PTS into the Spacing evaluation model of the following formula to obtain the corresponding OFDM signal dispersion estimate S

where, is the estimated value of OFDM signal dispersion, for /> The kth frequency domain signal in , /> for /> mean value.

Those skilled in the art can understand that all or part of the processes of the methods in the above embodiments can be implemented by instructing related hardware through computer programs, and the programs can be stored in a computer-readable storage medium. Wherein, the computer-readable storage medium is a magnetic disk, an optical disk, a read-only memory or a random access memory, and the like.

The above is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention shall be covered within the scope of protection of the present invention.

Claims (4)

1. The PTS peak-to-average ratio optimization method based on the frequency domain preprocessing is characterized by comprising the following steps:

performing frequency domain conversion on an input M-QAM signal, and performing signal segmentation on an OFDM frequency domain signal obtained by frequency domain conversion;

sequentially inputting each divided OFDM frequency domain sub-signal into a preset frequency domain scrambling model to obtain a plurality of discrete OFDM results after PTS multiplicative scrambling corresponding to the OFDM frequency domain signals;

inputting the discrete OFDM result after each PTS multiplicative scrambling into a preset Spacing evaluation model to obtain a corresponding OFDM signal dispersion estimation value;

searching a discrete OFDM result corresponding to the minimum value of the discrete estimated value of the OFDM signal, and performing IFFT (inverse fast Fourier transform) to obtain a time domain transmission signal with suppressed peak-to-average ratio;

the preset frequency domain scrambling model is that

In the method, in the process of the invention, represents V corresponding to OFDM frequency domain signal-! Discrete OFDM result after PTS multiplicative scrambling, Q _iv An ith row and a v term element which are the full space Q of the multiplicative scrambling sequence;

the frequency domain converting of the input M-QAM signal further includes:

carrying out OFDM frequency domain framing on the input M-QAM signal to obtain an OFDM frequency domain signal X corresponding to the M-QAM signal:

X＝[X ₁ ，…，X _i ，…，X _N ]

wherein X is _i For an OFDM frequency domain signal transmitted on the ith subcarrier, N represents the number of subcarriers of the OFDM frequency domain signal;

the signal segmentation is performed on the OFDM frequency domain signal obtained by frequency domain conversion, and the method further comprises the following steps:

dividing OFDM frequency domain signals into mutually disjoint subblocks by a random dividing method, wherein each subblock is used as an OFDM frequency domain subblock X _v ；

Wherein, X represents OFDM frequency domain signal, V represents total number of divided sub-blocks, subscript V represents sub-block order, V is {1,2, …, V };

inputting each divided OFDM frequency domain sub-signal into a preset frequency domain scrambling model in sequence to obtain a plurality of discrete OFDM results after PTS multiplicative scrambling corresponding to the OFDM frequency domain signals, and further comprising:

each OFDM frequency domain sub-signal X is obtained by the following formula _v Corresponding rotary phase factor b _v

b _v ＝e ^j2πi/V |i＝1，…，V

Wherein, | is a conditional operator;

according to the above rotary phase factor b _v Permutation and combination in the following formula are carried out to obtain the full space Q of the multiplicative scrambling sequence in the frequency domain scrambling model

All OFDM frequency domain sub-signals X _v Sequentially inputting a preset frequency domain scrambling model to obtain V-! Discrete OFDM result after PTS multiplicative scrambling

2. The PTS peak-to-average ratio optimizing method based on frequency domain preprocessing of claim 1, wherein the Spacing evaluation model is

Where S is the estimated value of the dispersion of OFDM signals,is->In (c) is the kth frequency domain signal,/is>Is->Is a mean value of (c).

3. A signal processing system based on frequency domain preprocessing, comprising:

the preprocessing module is used for carrying out frequency domain conversion on the input M-QAM signal, carrying out signal segmentation on the OFDM frequency domain signal obtained by the frequency domain conversion, and transmitting each segmented OFDM frequency domain sub-signal to the signal generation and screening module;

the signal generation and screening module is used for sequentially inputting each OFDM frequency domain sub-signal into a preset frequency domain scrambling model to obtain a discrete OFDM result after multiple PTS multiplicative scrambling corresponding to the OFDM frequency domain signal; inputting the discrete OFDM result after each PTS multiplicative scrambling into a preset Spacing evaluation model to obtain a corresponding OFDM signal dispersion estimation value; selecting a discrete OFDM result corresponding to the minimum value of the estimated value of the dispersion of the OFDM signal, and transmitting the discrete OFDM result to an output module;

the output module is used for performing IFFT conversion on the received discrete OFDM result to obtain a time domain transmission signal with suppressed peak-to-average ratio;

the signal generation and screening module executes the following procedure to obtain a plurality of discrete OFDM results after PTS multiplicative scrambling corresponding to the OFDM frequency domain signal:

each OFDM frequency domain sub-signal X is obtained by the following formula _v Corresponding rotary phase factor b _v

b _v ＝e ^j2πi/V |i＝1，…，V

Wherein, | is a conditional operator;

according to the above rotary phase factor b _v Permutation and combination in the following formula are carried out to obtain the full space Q of the multiplicative scrambling sequence in the frequency domain scrambling model

All OFDM frequency domain sub-signals X _v Sequentially inputting a preset frequency domain scrambling model in the following formula to obtain V-! Discrete OFDM result after PTS multiplicative scrambling

In which Q _iv An ith row and a v term element which are the full space Q of the multiplicative scrambling sequence;

the preprocessing module executes the following program:

carrying out OFDM frequency domain framing on the input M-QAM signal to obtain an OFDM frequency domain signal X corresponding to the M-QAM signal:

X＝[X ₁ ，…，X _i ，…，X _N ]

wherein X is _i For an OFDM frequency domain signal transmitted on the ith subcarrier, N represents the number of subcarriers of the OFDM frequency domain signal;

dividing OFDM frequency domain signals into mutually disjoint subblocks by a random dividing method, wherein each subblock is used as an OFDM frequency domain subblock X _v

Where V represents the total number of partitioned sub-blocks, subscript V represents the order of sub-blocks, V ε {1,2, …, V };

and sequentially transmitting each divided OFDM frequency domain sub-signal to a signal generation and screening module.

4. A signal processing system based on frequency domain preprocessing as claimed in claim 3, wherein said signal generation and filtering module performs the following procedure to obtain an OFDM signal dispersion estimate:

inputting the discrete OFDM result after each PTS multiplicative scrambling into a Spacing evaluation model of the following formula to obtain a corresponding OFDM signal dispersion estimated value S

Wherein S is OFDM signal dispersion estimates,is->In (c) is the kth frequency domain signal,/is>Is->Is a mean value of (c).