CN112968855B - A PTS peak-to-average ratio suppression method and data processing system based on space optimization - Google Patents

Abstract

The invention relates to a PTS peak-to-average ratio suppression method based on space optimization, belongs to the technical field of efficiency optimization of wireless communication power amplifiers, and solves the problem that the prior art cannot simultaneously take peak-to-average ratio suppression and complexity reduction into consideration. The method comprises: performing frequency domain conversion on an input M-QAM signal, generating an OFDM frequency domain signal, and performing signal segmentation on it; inputting each divided OFDM frequency domain sub-signal in turn into a preset frequency domain scrambling model, Obtain the frequency-domain discrete signals after multiple PTS multiplicative scrambling corresponding to the OFDM frequency-domain signal; respectively input the above-mentioned PTS multiplicative scrambled frequency-domain discrete signals into the preset Spacing evaluation model to obtain the corresponding signal Dispersion estimated value, arrange the estimated values from small to large, and identify the frequency domain discrete signals corresponding to the first m estimated values; perform time domain PAPR evaluation on each frequency domain discrete signal obtained from the above identification, based on the minimum evaluation result The corresponding frequency-domain discrete signal obtains the final peak-to-average ratio suppressed time-domain transmission signal.

Description

A PTS peak-to-average ratio suppression method and data processing system based on space optimization

technical field

The invention relates to the technical field of efficiency optimization of wireless communication power amplifiers, in particular to a PTS peak-to-average ratio suppression method based on space optimization and a data processing system.

Background technique

Multicarrier modulation is crucial to the realization of UWB systems. The problem of energy consumption in analog modulation becomes more prominent when the transmission bandwidth reaches its limit. Power amplifiers will dominate the energy consumption of base stations in any type of wireless communication, and the peak-to-average ratio (PAPR) problem will become more prominent in future communication systems. Relying on frequency bands such as millimeter wave and terahertz, the demand for ultra-broadband can be realized, and at the same time, it is also facing ultra- The defect of insufficient energy conversion rate of high-frequency power amplifier.

Considering the low hardware cost, optimizing the power amplifier distortion from the signal point of view is mainly to use the existing PAPR suppression algorithm to reduce the probability of the signal appearing in the distortion area. Existing PAPR suppression algorithms include pre-distortion methods (limiting algorithm, constellation extension ACE algorithm,) and partial transmission sequence (PTS) and so on. Predistortion methods are the most widely used in the engineering field. However, as high-order QAM modulation becomes the mainstream of 5G and future communications, the movement of vectors in the inner layers of constellation diagrams with a very high proportion is limited and cannot contribute to peak optimization. Compared with pre-distortion methods, PTS has a better signal peak-to-average ratio suppression effect, and has compatibility with ultra-wideband high-order QAM systems.

However, the existing PTS has extremely high computational complexity, and it is usually necessary to make a compromise between peak-to-average ratio suppression performance and computational complexity. Under the constraints of implementation complexity, the theoretical optimal solution cannot be obtained, and there are extreme Big room for improvement.

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 suppression method based on space optimization, so as to solve the problem that the prior art cannot take both peak-to-average ratio suppression and complexity reduction into consideration.

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

Carry out frequency domain conversion to the input M-QAM signal, generate OFDM frequency domain signal, carry out signal division to described OFDM frequency domain signal;

Each divided OFDM frequency domain sub-signal is sequentially input into a preset frequency domain scrambling model to obtain frequency domain discrete signals after multiple PTS multiplicative scrambling corresponding to the OFDM frequency domain signal;

Input the frequency-domain discrete signals after multiplicative scrambling of each PTS mentioned above into the preset Spacing evaluation model to obtain the corresponding estimated value of signal dispersion, arrange the estimated values from small to large, and identify the top m estimates in the arrangement The frequency-domain discrete signal corresponding to the value;

Time-domain PAPR evaluation is performed on each frequency-domain discrete signal obtained from the above identification, and the final peak-to-average ratio-suppressed time-domain transmission signal is obtained based on the frequency-domain discrete signal corresponding to the minimum evaluation result.

The beneficial effects of the above-mentioned technical solutions are as follows: the main disadvantage of the existing PTS is that IFFT transformation, PAPR time-domain evaluation, and combined search increase the computational complexity and computing power expenditure of the system sharply. Under the constraints of system implementation complexity, peak-to-average ratio suppression It is difficult to achieve the optimal solution for the effect compromise scheme, and there is a lot of room for optimization. The above technical solution proposes a PTS peak-to-average ratio suppression method optimized in the frequency domain. A small number of discrete signals in the frequency domain containing the optimal solution are selected from the entire space through the frequency domain Spacing evaluation, and then the optimal interference signal is accurately located by the time domain PAPR evaluation. The code sequence corresponds to a discrete OFDM signal (that is, the frequency-domain discrete signal corresponding to the minimum evaluation result), and the best effect of PAPR suppression is obtained under the condition that the complexity does not increase significantly.

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

Perform OFDM frequency domain framing on the input M-QAM signal to obtain the subcarriers corresponding to the modulation segments of each frame;

According to all the subcarriers obtained above, establish the OFDM frequency domain signal X corresponding to the M-QAM signal

X＝[X ₁ ,…,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 further includes:

By random segmentation method, the OFDM frequency domain signal is divided into frequency domain, and divided into mutually disjoint sub-blocks, and each sub-block is used 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: dividing the OFDM frequency domain signal into sub-blocks can improve the degree of freedom of scrambling, a higher number of blocks can obtain a higher degree of constellation dispersion, and can effectively reduce the probability of peak generation. Sub-block partitioning can achieve an effective trade-off between PTS complexity and peak-to-average ratio suppression performance.

Further, all sub-blocks are equal in size and orthogonal to each other, and elements in each sub-block are independent of each other.

The beneficial effect of the above further improvement scheme is that it can ensure that each sub-block does not interfere with other sub-blocks when multiplicative scrambling is performed, and the signal quality is fully guaranteed.

Further, the step of inputting each of the divided OFDM frequency domain sub-signals into a preset frequency domain scrambling model in sequence to obtain multiple PTS multiplicatively scrambled frequency domain discrete signals corresponding to the OFDM frequency domain signal, further include:

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

Perform all possible permutations and combinations of the above rotating phase factors b _v 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 frequency domain scrambling model in the following formula in sequence to obtain the V corresponding to the OFDM frequency domain signal! Frequency domain discrete signal 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 effect of the above-mentioned further improvement scheme is: the above-mentioned frequency-domain scrambling method is a multiplicative scrambling method, which can optimize the signal dispersion, and perform corresponding multiplicative descrambling at the receiving end. Effectively reduce the peak-to-average ratio.

Further, the Spacing evaluation model is

为

中的第k个频域信号，

为

的均值。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 Spacing frequency-domain dispersion evaluation through the above-mentioned Spacing evaluation model can predict the signal with a low peak-to-average ratio with a higher probability, and obtain an excellent PTS with lower complexity and easier The peak-to-average ratio suppresses the scrambled signal.

Further, time-domain PAPR evaluation is performed on each frequency-domain discrete signal obtained from the above identification, and the frequency-domain discrete signal corresponding to the minimum evaluation result is obtained, and the time-domain transmission signal after peak-to-average ratio suppression is obtained based on the frequency-domain discrete signal. steps, further comprising:

进行频域随机分割，划分为互不相交的子块X_iv′，所有频域离散信号都划分为相同大小的V个子块Each discrete signal in the frequency domain

Randomly divide the frequency domain into disjoint sub-blocks X _iv ′, all discrete signals in the frequency domain are divided into V sub-blocks of the same size

各自对应的Q_iv，根据下面公式对

进行时域PTS乘性加扰，获得m个时域加扰后的OFDM时域信号

Perform N-IFFT time domain transformation on each sub-block to obtain m frequency domain discrete signals

Corresponding Q _iv , according to the following formula

Perform time-domain PTS multiplicative scrambling to obtain m OFDM time-domain signals after time-domain scrambling

i∈[1,...,m]

分别进行下面公式中的PAPR评估，识别最小评估结果对应的时域加扰后的OFDM时域信号，作为时域传输OFDM信号

OFDM time domain signal after m time domain scrambling

Carry out the PAPR evaluation in the following formula respectively, identify the OFDM time domain signal corresponding to the time domain scrambled by the minimum evaluation result, and use it as the time domain transmission OFDM signal

k∈[1,…,N]

为

中的第k个元素，argmin()表示取最小值函数。In the formula,

for

The kth element in , argmin() means to take the minimum value function.

The beneficial effect of the above further improvement scheme is: according to the frequency domain Spacing evaluation, m row elements are selected from the full space Q of the multiplicative scrambling code sequence, which can accurately contain the optimal solution compared with m randomly sampled signals, and in the time domain dimension During the PAPR evaluation process, the optimal solution and the optimal OFDM signal (the time-domain transmission signal after the final peak-to-average ratio suppression) are accurately located.

Further, the method also includes the step of determining the optimal m value:

The N subcarriers of the OFDM frequency domain signal to be transmitted in the training data are divided into V groups of mutually disjoint sub-blocks, and the frequency domain scrambling model is input to perform frequency domain scrambling;

Set the initial m=1, input each frequency-domain scrambled discrete signal into the Spacing evaluation model to obtain an estimated value of signal dispersion, arrange the estimated values from small to large, and identify the first m estimated values in the arrangement corresponding to The corresponding Q _iv of the discrete signal establishes the optimal space;

Perform time-domain PAPR evaluation on each frequency-domain discrete signal obtained from the above identification according to the optimal space, and obtain the frequency-domain discrete signal corresponding to the minimum evaluation result;

Compare whether the frequency-domain discrete signal corresponding to the minimum evaluation result is the same as the V! Optimal Solution Fit in Full Space

If the optimal solution is not included, set m=m+1, and repeat the above steps until the optimal solution is included, as the optimal m value.

The beneficial effect of the above-mentioned further improvement scheme is: the minimum optimal space containing the optimal solution is obtained through offline training, that is, the optimal m value, and by reducing the optimal space, the number of searches is reduced, the complexity and delay are reduced, and the optimal solution is accelerated. The convergence rate of the optimal solution.

On the other hand, an embodiment of the present invention provides a data processing system based on space optimization, including sequentially connected:

A preprocessing module, configured to perform frequency domain conversion on the input M-QAM signal to generate an OFDM frequency domain signal; and perform signal segmentation on the OFDM frequency domain signal to generate OFDM frequency domain sub-signals and transmit them to the data processing module;

A data processing module, configured to sequentially input each received OFDM frequency domain sub-signal into a preset frequency domain scrambling model to obtain multiple PTS multiplicatively scrambled frequency domain discrete signals corresponding to the OFDM frequency domain signal and, input the frequency-domain discrete signals of each of the above-mentioned PTS multiplicative scrambled signals into the preset Spacing evaluation model to obtain corresponding signal dispersion estimated values; and arrange all the estimated values from small to large, and identify the The frequency-domain discrete signals corresponding to the first m estimated values are transmitted to the signal generation module;

The signal generation module is configured to perform time-domain PAPR evaluation on each received frequency-domain discrete signal, and obtain a final peak-to-average ratio-suppressed time-domain transmission signal based on the frequency-domain discrete signal corresponding to the minimum evaluation result.

The beneficial effect of the above technical solution is: the main disadvantage of the existing PTS is that the IFFT transformation, PAPR time domain evaluation, and combined search make the computational complexity and computing power expenditure of the system increase sharply. It is difficult to achieve the optimal solution for the effect compromise scheme, and there is a lot of room for optimization. The above system is a PTS peak-to-average ratio suppression scheme optimized in the frequency domain. A small number of discrete signals in the frequency domain containing the optimal solution are optimized from the entire space through the frequency domain Spacing evaluation, and then the optimal scrambling code sequence is accurately located by the time domain PAPR evaluation. Corresponding to the discrete OFDM signal (that is, the frequency-domain discrete signal corresponding to the minimum evaluation result), the best effect of PAPR suppression is obtained under the condition that the complexity does not increase significantly.

Based on the further improvement of the above system, the frequency domain scrambling model is

为PTS乘性加扰后的频域离散信号，X_v为OFDM频域子信号，i＝1,…,V！；In the formula, Q _iv is the item v element of the i-th row of the full space Q of the multiplicative scrambling code sequence,

is the frequency-domain discrete signal after PTS multiplicative scrambling, X _v is the OFDM frequency-domain sub-signal, i=1,...,V! ;

The Spacing evaluation model is

为

中的第k个频域信号，

为

的均值。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: from the PTS candidate OFDM frequency domain signal of the whole space (frequency domain discrete signal after multiple PTS multiplicative scrambling), carry out Spacing evaluation, predict low peak-to-average ratio OFDM signal (prem The frequency-domain discrete signal corresponding to each estimated value) is optimized to select a targeted candidate signal, which can ensure that the optimal solution can be quickly located and searched with low complexity (the time-domain transmission signal after the final peak-to-average ratio suppression).

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.

Figure 1 is a schematic diagram of the steps of the PTS peak-to-average ratio suppression method based on spatial optimization in Example 1 of the present invention;

2 is a schematic diagram of the principle of the PTS peak-to-average ratio suppression method based on space optimization in Embodiment 1 of the present invention;

3 is a schematic diagram of the composition of a data processing system based on space optimization in Embodiment 3 of the present invention;

Figure 4 is a schematic diagram of the peak-to-average ratio suppression performance of the method of the embodiment of the present invention when m=4;

Fig. 5 is a schematic diagram of the peak-to-average ratio suppression performance of the method of the embodiment of the present invention when m=40.

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 suppression method based on space optimization, as shown in Figure 1, including the following steps:

S1. Perform frequency domain conversion on the input M-QAM signal to generate an OFDM frequency domain signal, and perform signal segmentation on the OFDM frequency domain signal;

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

S3. Input the frequency-domain discrete signals of each of the above-mentioned PTS multiplicative scrambled signals into the preset Spacing evaluation model to obtain the corresponding signal dispersion estimated value, arrange the estimated values from small to large, and identify the top m in the arrangement The discrete signal in the frequency domain corresponding to an estimated value;

S4. Perform time-domain PAPR evaluation on each frequency-domain discrete signal obtained from the above identification, and obtain a final peak-to-average ratio-suppressed time-domain transmission signal based on the frequency-domain discrete signal corresponding to the minimum evaluation result.

Compared with the prior art, the complexity of the method provided by this embodiment is revealed. The main disadvantage of the existing PTS is that IFFT transformation, PAPR time-domain evaluation, and combined search increase the computational complexity and computing power cost of the system dramatically. Under the constraints of system implementation complexity, it is difficult to achieve the optimal peak-to-average ratio suppression effect compromise Therefore, there is a large room for optimization. The above method proposes a PTS peak-to-average ratio suppression scheme optimized in the frequency domain. A small number of discrete signals in the frequency domain containing the optimal solution are selected from the entire space through the frequency domain Spacing evaluation, and then the optimal scrambling code is accurately located by the time domain PAPR evaluation. The sequence corresponds to the discrete OFDM signal (that is, the frequency-domain discrete signal corresponding to the minimum evaluation result), and the best effect of PAPR suppression is obtained under the condition that the complexity does not increase significantly.

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, and obtain the subcarriers corresponding to the modulation segments of each frame; the time intervals corresponding to the modulation segments of each frame are the same;

S12. According to all the subcarriers obtained above, establish the OFDM frequency domain signal X corresponding to the M-QAM signal

X＝[X ₁ ,…,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;

S13. Carry out frequency-domain segmentation to the OFDM frequency-domain signal by a random segmentation method, and be divided into disjoint sub-blocks. The sub-carriers of the sub-blocks are in different bandwidths), each element in each sub-block is independent of each other (the frequency of each sub-carrier of each sub-block is different), each sub-block is used 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}.

Preferably, each sub-block is divided into an effective carrier bit and a virtual carrier bit, the effective carrier bit is a sub-carrier obtained by frequency domain segmentation, and the virtual carrier position is 0, wherein the effective carrier bit of each sub-block is a virtual carrier in other sub-blocks .

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

b _v ＝e ^j2πi/V |i＝1,...,V (3)

S22. Perform all possible permutations and combinations of the above-mentioned rotational phase factors b _v to obtain the full space Q of the multiplicative scrambling code sequence in the frequency domain scrambling model

V! =V·(V-1)...1

Exemplarily, when V=3

S23. Input all OFDM frequency-domain sub-signals Xv into the frequency-domain scrambling model in the following formula in order to obtain the _V corresponding to the OFDM frequency-domain signal! Frequency domain discrete signal 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 preset Spacing evaluation model in step S3 is

为

中的第k个频域信号，

为

的均值。In the formula, S is the estimated value of OFDM signal dispersion,

for

The kth frequency domain signal in ,

for

mean value.

作为离散的中心点，S值越小，离散度越高。高峰均比主要由相似相位多载波叠加产生，而离散度越高的信号，产生高峰均比的概率更小。

As a discrete central point, the smaller the S value, the higher the discreteness. The peak-to-average ratio is mainly generated by the superposition of multiple carriers with similar phases, and the signal with higher dispersion has a smaller probability of generating the peak-to-average ratio.

The value of m is preset, and the setting method will be described in detail later. Use offline training and search to obtain a static minimum m value (optimum m value) to reduce the complexity of implementation. Once the m value is confirmed, it can be called directly in the application.

Step S3 preselects m alternative frequency-domain discrete signals with relatively low peak-average values; then converts each selected frequency-domain discrete signal to the time domain through step S4, and performs time-domain PTS multiplicative scrambling to add The time-domain PAPR evaluation is performed on the scrambled signal, and the time-domain scrambled signal corresponding to the minimum PAPR evaluation result is searched, and used as the time-domain transmission signal after the final peak-to-average ratio suppression.

Preferably, step S4 is further refined as:

进行频域随机分割，划分为互不相交的子块X_iv′，所有频域离散信号都划分为相同大小的V个子块S41. Each discrete signal in the frequency domain

Randomly divide the frequency domain into disjoint sub-blocks X _iv ′, all discrete signals in the frequency domain are divided into V sub-blocks of the same size

各自对应的Q_iv，根据下面公式对

进行时域PTS乘性加扰，获得m个时域加扰后的OFDM时域信号

S42. Perform N-IFFT time-domain transformation on each sub-block to obtain m frequency-domain discrete signals

Corresponding Q _iv , according to the following formula

Perform time-domain PTS multiplicative scrambling to obtain m OFDM time-domain signals after time-domain scrambling

i∈[1,...,m]

分别进行下面公式中的PAPR评估，识别最小评估结果对应的时域加扰后的OFDM时域信号，作为时域传输OFDM信号

S43. OFDM time domain signals after m time domain scrambling

Carry out the PAPR evaluation in the following formula respectively, identify the OFDM time domain signal corresponding to the time domain scrambled by the minimum evaluation result, and use it as the time domain transmission OFDM signal

k∈[1,…,N]

为

中的第k个元素，argmin()表示取最小值函数。In the formula,

for

The kth element in , argmin() means to take the minimum value function.

Preferably, the space-optimized PTS peak-to-average ratio suppression method also includes the step of determining the optimal m value:

S01. Divide the N subcarriers of the OFDM frequency domain signal to be transmitted in the training data into V groups of mutually disjoint sub-blocks, and input the frequency domain scrambling model to perform frequency domain scrambling;

S02. Set the initial m=1, input each frequency-domain scrambled discrete signal into the Spacing evaluation model to obtain an estimated value of signal dispersion, arrange the estimated values from small to large, and identify the first m estimates in the arrangement Q _iv corresponding to the discrete signal corresponding to the value, to establish an optimal space;

S03. Perform time-domain PAPR evaluation on each frequency-domain discrete signal obtained from the above identification according to the optimal space, and obtain the frequency-domain discrete signal corresponding to the minimum evaluation result;

S04. Compare whether the frequency-domain discrete signal corresponding to the minimum evaluation result is the same as V! Optimal Solution Fit in Full Space

为

的期望。In the formula,

for

expectations.

S05. If the optimal solution is not included, set m=m+1, repeat the above steps until the optimal solution is included, as the optimal m value this time, and complete the training of all training data in sequence.

Compared with Example 1, the principle of the method provided in this example is shown in Figure 2. The CCDF probability density curve in a large sample space is steady state, and a static minimum value of m can be obtained by means of offline training. Reduce the complexity of implementation, and the offline training process will not introduce computational complexity.

Example 3

The present invention also provides a data processing system corresponding to the methods of Embodiments 1 and 2, as shown in FIG. 3 , including a preprocessing module, a data processing module, and a signal generating module connected in sequence.

The preprocessing module is used to perform frequency domain conversion on the input M-QAM signal to generate an OFDM frequency domain signal; and perform signal segmentation on the OFDM frequency domain signal to generate OFDM frequency domain sub-signals and transmit them to the data processing module.

A data processing module, configured to sequentially input each received OFDM frequency domain sub-signal into a preset frequency domain scrambling model to obtain multiple PTS multiplicatively scrambled frequency domain discrete signals corresponding to the OFDM frequency domain signal and, input the frequency-domain discrete signals of each of the above-mentioned PTS multiplicative scrambled signals into the preset Spacing evaluation model to obtain corresponding signal dispersion estimated values; and arrange all the estimated values from small to large, and identify the The frequency-domain discrete signals corresponding to the first m estimated values are transmitted to the signal generation module.

Preferably, the preset frequency domain scrambling model is

为PTS乘性加扰后的频域离散信号，X_v为OFDM频域子信号，i＝1,…,V！。In the formula, Q _iv is the item v element of the i-th row of the full space Q of the multiplicative scrambling code sequence,

is the frequency-domain discrete signal after PTS multiplicative scrambling, X _v is the OFDM frequency-domain sub-signal, i=1,...,V! .

The default Spacing evaluation model is

为

中的第k个频域信号，

为

的均值。In the formula, S is the estimated value of OFDM signal dispersion,

for

The kth frequency domain signal in ,

for

mean value.

The signal generation module is configured to perform time-domain PAPR evaluation on each received frequency-domain discrete signal, and obtain a final peak-to-average ratio-suppressed time-domain transmission signal based on the frequency-domain discrete signal corresponding to the minimum evaluation result.

The performance comparison between the existing PTS (traditional PTS) and the FTD-PTS optimized in the frequency domain of this embodiment will be analyzed below through experiments. First, the number of carriers in the OFDM signal is set to N=1024, the number of upsampling in the OFDM system L=4, the number of subcarriers in the PTS technology V=6, and the method of random division is used for the existing PTS and the FTD-PTS method of this embodiment Carry out experimental simulation, as shown in Figure 4-5. When m=4, at CCDF=10 ^-3 , the PAPR performance of FTD-PTS is much better than the existing PTS algorithm, and there is 1.5dB peak-to-average ratio suppression gain. When m=40, the PAPR performance of FTD-PTS overlaps with the theoretical extremum, which is equivalent to obtaining the optimal solution. Among them, m=40 is close to the universal selection threshold of the traditional PTS actual search implementation complexity and acceptable time delay. It can be seen that the implementation complexity of the method in this embodiment is significantly reduced on the premise of maintaining the existing PTS peak-to-average ratio suppression performance.

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 person skilled in the art within the technical scope disclosed in the present invention can easily think of changes or Replacement should be covered within the protection scope of the present invention.

Claims (8)

1. A PTS peak-to-average power ratio (PAPR) suppression method based on spatial optimization is characterized by comprising the following steps of:

performing frequency domain conversion on an input M-QAM signal to generate an OFDM frequency domain signal, and performing signal segmentation on the OFDM frequency domain signal;

the step of signal-dividing the OFDM frequency domain signal further includes:

the OFDM frequency domain signal is divided into sub-blocks which are not intersected with each other by a random division method, and each sub-block is used as an OFDM frequency domain sub-signal X _v

In the formula, V represents the total number of segmented subblocks, subscript V represents subblock order, and V belongs to {1,2, \8230;, V };

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

the step of sequentially inputting each divided OFDM frequency domain sub-signal into a preset frequency domain scrambling model to obtain a plurality of PTS multiplicative scrambled frequency domain discrete signals corresponding to the OFDM frequency domain signal further includes:

obtaining each OFDM frequency domain sub-signal X by the following formula _v Corresponding rotational phase factor b _v

b _v ＝e ^j2πi/V |i＝1,…,V

Rotating the phase factor b _v All possible permutation and combination are carried out to obtain multiplicative scrambling code sequence in the frequency domain scrambling modelColumn total space Q

All OFDM frequency domain sub-signals X _v Sequentially inputting the frequency domain scrambling model in the following formula to obtain V | corresponding to the OFDM frequency domain signal! Frequency domain discrete signal after PTS multiplicative scrambling

In the formula, Q _iv Is the ith row and the v item element of the multiplicative scrambling sequence total space Q;

respectively inputting the frequency domain discrete signals after multiplicative scrambling of each PTS into a preset Spacing evaluation model to obtain corresponding signal dispersion estimation values, arranging the estimation values from small to large, and identifying the frequency domain discrete signals corresponding to the first m estimation values in the arrangement;

and respectively performing time domain PAPR evaluation on each frequency domain discrete signal obtained by the identification, and obtaining a time domain transmission signal after the peak-to-average ratio is finally inhibited based on the frequency domain discrete signal corresponding to the minimum evaluation result.

2. The method for suppressing PTS peak-to-average power ratio based on spatial preference of claim 1, wherein said step of performing frequency domain conversion on the input M-QAM signal to generate an OFDM frequency domain signal further comprises:

carrying out OFDM frequency domain framing on the input M-QAM signal to obtain a subcarrier corresponding to each frame modulation fragment;

establishing an OFDM frequency domain signal X corresponding to the M-QAM signal according to all the obtained subcarriers

X＝[X ₁ ,…,X _N ]

In the formula, X _i Is OFDThe ith subcarrier of the M frequency domain signal, N represents the number of subcarriers of the OFDM frequency domain signal.

3. The method of claim 2, wherein all sub-blocks are equal in size and orthogonal to each other, and the elements in each sub-block are independent.

4. The PTS peak-to-average power ratio suppression method according to claim 3, wherein the Spacing evaluation model is

Wherein S is an estimated value of dispersion of the OFDM signal,

is composed of

The k-th frequency-domain signal of (a),

is composed of

Is measured.

5. The PTS PAPR suppression method according to claim 4, wherein the step of performing time domain PAPR estimation on each frequency domain discrete signal obtained by the identification to obtain the frequency domain discrete signal corresponding to the minimum estimation result, and obtaining the time domain transmission signal after PAPR suppression based on the frequency domain discrete signal further comprises:

dispersing each frequency domain signal

Performing frequency domain random partition, and dividing into mutually disjoint sub-blocks X _iv ', all frequency-domain discrete signals are divided into V sub-blocks of the same size

Performing N-IFFT time domain transformation on each sub-block to obtain m frequency domain discrete signals

Each corresponding Q _iv According to the following formula

Time domain PTS multiplicative scrambling is carried out to obtain m OFDM time domain signals after time domain scrambling

i∈[1,…,m]

OFDM time domain signal after scrambling m time domains

Respectively carrying out PAPR evaluation in the following formula, identifying the OFDM time domain signal after time domain scrambling corresponding to the minimum evaluation result, and using the OFDM time domain signal as a time domain transmission OFDM signal

k∈[1,…,N]

In the formula (I), the compound is shown in the specification,

is composed of

The kth element in (1), argmin () represents the take minimum function.

6. The PTS peak-to-average ratio suppression method based on spatial preference according to one of claims 1 to 5, further comprising the step of determining an optimal m-value:

dividing N subcarriers of an OFDM frequency domain signal to be transmitted in training data into V groups of mutually disjoint sub-blocks, and inputting the sub-blocks into the frequency domain scrambling model to perform frequency domain scrambling;

setting initial m =1, inputting the discrete signal after scrambling of each frequency domain into the Spacing evaluation model to obtain a signal dispersion estimation value, arranging the estimation values from small to large, and identifying Q corresponding to the discrete signals corresponding to the previous m estimation values in the arrangement _iv Establishing a preferred space;

respectively performing time domain PAPR evaluation on each frequency domain discrete signal obtained by identification according to an optimal space to obtain a frequency domain discrete signal corresponding to a minimum evaluation result;

comparing whether the frequency domain discrete signal corresponding to the minimum evaluation result is with V! Optimal solution anastomosis in full space

And if the optimal solution is not contained, enabling m = m +1, and repeating the steps until the optimal solution is contained as the optimal m value.

7. A space-based preference data processing system, comprising:

a pre-processing module for performing frequency domain to the input M-QAM signalConverting to generate OFDM frequency domain signals; performing signal segmentation on the OFDM frequency domain signal to generate an OFDM frequency domain sub-signal and transmitting the OFDM frequency domain sub-signal to a data processing module; the step of signal-dividing the OFDM frequency domain signal further includes: the OFDM frequency domain signal is divided into sub-blocks which are not intersected with each other by a random division method, and each sub-block is used as an OFDM frequency domain sub-signal X _v

In the formula, V represents the total number of subblocks partitioned, the subscript V represents the subblock order, and V belongs to {1,2, \\ 8230;, V };

the data processing module is used for sequentially inputting each received OFDM frequency domain sub-signal into a preset frequency domain scrambling model to obtain frequency domain discrete signals after multiplicative scrambling of various PTS corresponding to the OFDM frequency domain signals; inputting the frequency domain discrete signals after multiplicative scrambling of each PTS into a preset Spacing evaluation model to obtain corresponding signal dispersion estimation values; arranging all the estimated values from small to large, identifying frequency domain discrete signals corresponding to the first m estimated values in the arrangement, and transmitting the frequency domain discrete signals to a signal generation module;

the step of sequentially inputting each received OFDM frequency domain sub-signal into a preset frequency domain scrambling model to obtain frequency domain discrete signals after multiple PTS multiplicative scrambling corresponding to the OFDM frequency domain signal further includes:

obtaining each OFDM frequency domain sub-signal X by the following formula _v Corresponding rotational phase factor b _v

b _v ＝e ^j2πi/V |i＝1,…,V

Where V denotes the total number of subblocks partitioned, the subscript V denotes the subblock order, V ∈ {1,2, \ 8230;, V }.

Rotating the phase factor b _v All possible permutation and combination are carried out to obtain the multiplicative scrambling code sequence total space Q in the frequency domain scrambling model

All OFDM frequency domain sub-signals X _v Sequentially inputting the frequency domain scrambling model in the following formula to obtain V | corresponding to the OFDM frequency domain signal! Frequency domain discrete signal after PTS multiplicative scrambling

In the formula, Q _iv Is the ith row and the v item element of the multiplicative scrambling sequence total space Q;

and the signal generation module is used for respectively carrying out time domain PAPR evaluation on each received frequency domain discrete signal and obtaining a time domain transmission signal after the final peak-to-average ratio is restrained based on the frequency domain discrete signal corresponding to the minimum evaluation result.

8. The space-based optimization data processing system of claim 7, wherein the Spacing evaluation model is

Wherein S is the OFDM signal dispersion estimated value,

is composed of

The k-th frequency-domain signal in (b),

is composed of

Is measured.

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