OFDM system PAPR suppression method based on HPSO

Abstract

The invention belongs to the technical field of wireless communication, and particularly relates to an OFDM (Orthogonal Frequency Division Multiplexing) system PAPR (Peak to Average Power Ratio) suppression method based on HPSO (High Performance Particle Swarm Optimization), which comprises the following steps of: 1, generating a plurality of candidate signals according to an OFDM system model, and applying different phase sequences to form a candidate signal set; 2, a particle swarm is initialized, each candidate signal is regarded as a particle, the fitness function of the particle swarm is a PAPR value, and the target is to find a phase combination with the lowest PAPR; 3, updating the speed and position of the particles based on a hierarchical particle swarm optimization algorithm, and gradually optimizing phase combination; and step 4, continuously iterating according to the historical optimal solution and the global optimal solution of the particle swarm until the optimal PAPR suppression effect is achieved. Compared with a traditional OFDM system peak-to-average ratio suppression method, the method has the advantages that the optimal phase sequence is selected from the candidate signals through the HPSO-SLM algorithm, a lower PAPR value is achieved, and the power amplification efficiency and transmission performance of the system are improved.

Description

Technical Field

[0001] The invention relates to the field of communication technology, and in particular to an OFDM system PAPR suppression method based on HPSO. Background Art

[0002] Orthogonal Frequency Division Multiplexing (OFDM) is an efficient multi-carrier modulation technology widely used in modern wireless communication systems such as LTE, 5G, Wi-Fi and DVB. OFDM can effectively combat multipath effects and frequency selective fading, thereby significantly improving the spectrum utilization of the system. However, since the OFDM signal is the result of the superposition of multiple subcarriers, its peak power may be much higher than the average power, resulting in a high peak-to-average power ratio (PAPR). High PAPR not only increases the nonlinear distortion of the power amplifier, but also reduces the energy efficiency and reliability of the system. In order to reduce the PAPR in OFDM systems, researchers have proposed a variety of algorithms, including signal clipping, coding, selective mapping (SLM) and partial transmission sequence (PTS).

[0003] Traditional PSO algorithms may fall into local optimality or converge slowly when dealing with high-dimensional complex optimization problems. In order to further improve the optimization efficiency of PSO-SLM and reduce the computational complexity, the present invention proposes a selective mapping algorithm (HPSO-SLM) based on hierarchical particle swarm optimization. HPSO-SLM introduces a hierarchical particle swarm structure, divides particles into multiple layers, screens and optimizes particles in each layer, and selects the best particles layer by layer to enter the next layer, reducing invalid search space, thereby improving the global search capability and convergence speed of the algorithm. This hierarchical strategy not only effectively reduces the computational overhead, but also reaches the global optimal solution more quickly when looking for signals that minimize PAPR. Therefore, HPSO-SLM can more efficiently adapt to the low power consumption and high efficiency requirements of modern networks while reducing PAPR. Summary of the invention

[0004] 1. Technical issues to be resolved

[0005] In view of the deficiencies of the prior art, the present invention provides an OFDM system PAPR suppression method based on HPSO, which solves the problems raised in the above background technology.

[0006] (II) Technical solution

[0007] In order to achieve the above-mentioned purpose, the present invention specifically adopts the following technical solutions:

[0008] A method for suppressing PAPR of an OFDM system based on HPSO comprises the following steps:

[0009] Initialize OFDM system parameters, including the number of subcarriers, modulation mode, number of symbols, etc., to generate the original OFDM signal.

[0010] Defines a method for calculating PAPR, and evaluates the PAPR performance of a signal by calculating the ratio of the peak power to the average power of the signal.

[0011] The phase sequence of OFDM symbols is optimized using a hierarchical particle swarm optimization algorithm to select the phase sequence with the lowest PAPR.

[0012] The optimized signal is re-transformed by IFFT, and its PAPR is calculated to compare the performance difference before and after optimization.

[0013] Furthermore, the hierarchical particle swarm optimization algorithm adopts a hierarchical structure, dividing the particle swarm into a main layer and several sub-layers, the main layer is responsible for global search, and the sub-layers are responsible for local optimization, thereby improving the global search capability and convergence speed of the algorithm.

[0014] Furthermore, the main layer updates the optimal results of all sub-layers by fusing them to ensure that the phase sequence with the minimum PAPR is selected globally, thus preventing the algorithm from falling into the local optimum.

[0015] Furthermore, particles in the sub-layer update their positions through dynamic adjustment of inertia weight, cognitive coefficient and social coefficient, and transmit their status to the main layer to achieve information interaction and optimization coordination between layers.

[0016] Furthermore, the phase sequence generated by the method adopts random initialization, and updates the distribution of the phases through iterative optimization, thereby enhancing the diversity of the search space and the optimization effect.

[0017] Furthermore, the method compares the PAPR of non-optimized signals, traditional SLM optimized signals and signals based on hierarchical particle swarm optimization, and presents the comparison results in CCDF curves to verify the advantages of hierarchical particle swarm optimization algorithm in reducing PAPR.

[0018] Furthermore, the method is applicable to any OFDM system parameter configuration, including the number of subcarriers, modulation mode (such as QPSK, 16QAM) and the number of signal symbols, and has strong robustness and practicality.

[0019] (III) Beneficial effects

[0020] Compared with the prior art, the present invention provides an OFDM system PAPR suppression method based on HPSO, which has the following beneficial effects:

[0021] 1. Significantly reduce PAPR performance

[0022] The present invention performs PAPR suppression through a hierarchical particle swarm optimization algorithm (HPSO), which can effectively select the combination with the lowest PAPR in multiple phase sequences and significantly reduce the PAPR of the OFDM signal. Compared with the traditional SLM method and single-layer PSO algorithm, the present invention has a significant improvement in PAPR suppression effect.

[0023] 2. Avoid local optimality and improve global optimization capabilities

[0024] The hierarchical structure allows for collaborative optimization between the main layer and the sub-layers. The main layer extracts the global optimal phase sequence from the best solution of the sub-layer, thereby preventing the algorithm from falling into the local optimum. Compared with the single-layer optimization of the ordinary PSO algorithm, the HPSO algorithm of the present invention has better global search capability and optimization stability.

[0025] 3. Diversified phase search to improve algorithm convergence speed

[0026] The multi-level structure of the hierarchical particle swarm introduces more diversity in phase search, and each sub-layer performs optimization tasks independently, which speeds up the convergence of the phase sequence. This hierarchical parallel optimization method has faster computational efficiency than traditional SLM and PSO algorithms.

[0027] 4. Lower computational complexity, suitable for real-time applications

[0028] The present invention effectively reduces the number of particles and iterations required for a single search through a hierarchical optimization structure, significantly reduces the computational complexity compared to the traditional PSO-SLM method, and is suitable for wireless communication systems with high real-time performance requirements. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 The system block diagram for suppressing the PAPR of OFDM system using hierarchical particle swarm algorithm;

[0030] Figure 2 This is a schematic diagram of the system framework structure of the present invention based on the hierarchical particle swarm algorithm to optimize the SLM algorithm;

[0031] Figure 3 It is an iterative optimization flow chart of the hierarchical particle swarm algorithm of the present invention;

[0032] Figure 4 It is a signal processing flow chart of the hierarchical particle swarm algorithm combined with SLM algorithm optimization of the present invention;

[0033] Figure 5 It is a schematic diagram comparing the peak-to-average ratio (PAPR) performance of the OFDM system before and after the optimization of the present invention. DETAILED DESCRIPTION

[0034] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0035] Example

[0036] like Figure 1 As shown, the present invention proposes an OFDM system PAPR suppression method based on HPSO, and its overall process is as follows:

[0037] At the transmitting end, binary serial high-speed data stream sends signal T X After M-ary quadrature phase shift keying (M-QAM / QPSK) modulation, frequency domain modulation symbols are generated, and then the serial data is converted into N parallel data through serial-to-parallel conversion and assigned to N mutually orthogonal subcarriers. It is converted to the time domain through inverse fast Fourier transform (IFFT) to generate OFDM symbols. The HPSO-SLM algorithm is used to generate the optimal phase sequence to suppress the PAPR of OFDM symbols. At the same time, the HPSO-SLM algorithm outputs the optimal phase sequence for subsequent OFDM symbol generation. Then, the optimal phase sequence is used to generate the PAPR-optimized OFDM signal, and the optimized OFDM signal is amplified to reduce nonlinear distortion. Finally, the signal is demodulated at the receiving end to restore the original data stream.

[0038] like Figure 2 As shown, the present invention proposes a PAPR suppression method for an OFDM system based on HPSO to reduce the peak-to-average ratio of an orthogonal frequency division multiplexing system.

[0039] The whole system includes the following modules:

[0040] 1. Input signal generation module: used to generate input OFDM modulation signal sequence;

[0041] 2. SLM candidate signal generation module: generates multiple candidate signal sequences using phase rotation factors;

[0042] 3. Hierarchical particle swarm optimization module: optimizes the phase rotation factor selection process and determines the optimal candidate signal;

[0043] 4. PAPR calculation and optimization result output module: calculate the PAPR value of the optimized signal and output the optimized signal.

[0044] Hierarchical Particle Swarm Optimization Process

[0045] like Figure 3 As shown, in some embodiments, the specific process of the hierarchical particle swarm algorithm is as follows:

[0046] 1. Initialize particle swarm:

[0047] First generate a random phase sequence for each particle:

[0048] b p =[b p，0 , b p，1 , …, b p,N-1 ], p = 1, ..., p

[0049] Each of the b p,k =e jθp,k , angle θ p,k is a random number uniformly distributed in [0,2π]. The position is then represented as the initial angle vector x of the phase sequence i,d (0), each component x i,d (0) = θ i,d ,Right now:

[0050] x i,d (0) = angle(b i,d ), i = 1, ..., P

[0051] 2. Layered iterative optimization:

[0052] The hierarchical structure is used to screen particles layer by layer, and the number of particles retained in each layer gradually decreases. The following is the parameter update and solution process in each layer. In each iteration of each layer, the speed of each particle is updated according to the inertia weight, cognitive and social components. The speed update formula of particle i in the dth dimension is:

[0053] v i,d (t+1)=w·v i,d (t)+c1·r1·(p i,d (t)-x i,d (t))+c2·r2(g d (t)-x i,d (t))

[0054] The inertia weight w controls the degree of speed maintenance, the cognitive coefficient c1 and the social coefficient c2 adjust the particle's dependence on its own experience and group experience, and the random numbers r1 and r2 follow the uniform distribution U(0,1), introducing randomness to promote search diversification. Local optimal position p i,d (t) and the global optimal position g d (t) is the phase sequence position with the smallest PAPR in history. The current position of the particle is updated according to the new velocity, that is, the formula for updating the particle position is:

[0055] xi,d (t+1)=x i,d (t)+v i,d (t+1)

[0056] 3. Selection of global optimal solution:

[0057] For each generated phase sequence b i Generate new candidate OFDM signal x i (n) and calculate its PAPR:

[0058]

[0059]

[0060] The current position of each particle is compared with its historical optimal position. If the current PAPR is smaller, the local optimal position of the particle is updated:

[0061]

[0062] Among them, PAPR (p i ) represents the PAPR corresponding to the particle's historical optimal position. Then, find the particle corresponding to the minimum PAPR value of the current particle group in each layer and update the global optimal position:

[0063]

[0064] At the end of each layer iteration, the top P is selected according to the PAPR value. l Particles enter the next layer of optimization, and the number of particles retained in each layer is half of the previous layer, that is, This gradually narrows the search space and improves optimization efficiency. At the end of the last layer, all retained particles have been screened through multiple layers, and the phase sequence corresponding to the particle with the smallest PAPR is selected as the final optimal phase sequence:

[0065]

[0066] Use the optimal phase sequence b opt Generate PAPR optimized OFDM signal x opt (n):

[0067]

[0068] The final x opt (n) is the OFDM signal optimized by HPSO-SLM, which has a lower PAPR and can effectively reduce the nonlinear distortion of the power amplifier and improve the transmission efficiency.

[0069] Signal processing flow combining SLM algorithm and HPSO

[0070] like Figure 4 As shown, in some embodiments, the specific steps of optimizing the SLM algorithm of the present invention are:

[0071] 1. Candidate signal generation: For each OFDM symbol, SLM optimizes PAPR by selecting different phase sequences. First, generate the phase sequence and define the number of phase sequences U. Each phase sequence is an N-dimensional vector P u =[P u,1 ,P u，2 ,…,P u,N ], whose elements are random phase factors, usually complex values ​​with unit amplitude and uniform distribution. The phase sequence is defined as:

[0072]

[0073] 2. Optimize phase selection: Each symbol X s , calculate the PAPR value after each phase sequence mapping. That is, using the phase sequence P u After modulating the OFDM symbol, the new symbol X is obtained s ·P u The IFFT result is:

[0074] X s,u =IFFT(X s ·P u )

[0075] Calculate the corresponding PAPR:

[0076]

[0077] 3. Output optimization results: Select the phase sequence P that minimizes PAPR u* :

[0078]

[0079] Then this optimized symbol Sent to the power amplifier and wireless channel module.

[0080] PAPR performance comparison and verification

[0081] like Figure 5 As shown, in some embodiments, the hierarchical particle swarm algorithm optimized SLM method of the present invention is compared with the traditional SLM method in terms of performance, and the test results show that:

[0082] 1. The optimized PAPR performance is better than the traditional SLM algorithm and can further reduce the PAPR with the same number of candidate signals;

[0083] 2. The computational complexity is significantly reduced, and the global search capability of the hierarchical particle swarm algorithm effectively reduces the number of iterations. Figure 3 As shown, in some embodiments, in the optimized hierarchical strategy, particles in the high fitness layer will guide particles in the low fitness layer in each iteration, forming a collaborative optimization mechanism, which improves the global search efficiency while reducing the risk of falling into the local optimum.

[0084] Peak-to-average ratio calculation module design

[0085] like Figure 3 As shown, in some embodiments, the peak-to-average ratio calculation process includes:

[0086] 1. Signal capture module: obtain the time domain signal output by the SLM algorithm;

[0087] 2. Peak detection module: calculates the maximum power of the signal;

[0088] 3. Mean calculation module: calculates the average power of the signal;

[0089] 4. PAPR output module: calculates the peak-to-average ratio and uses it as the input of the optimization fitness function.

[0090] Additional Notes

[0091] like Figure 5 As shown in the figure, the experimental results show that the present invention can reduce the PAPR of the OFDM system while ensuring that the bit error rate performance of the signal will not be significantly deteriorated. Through the multi-level optimization design of the hierarchical particle swarm algorithm, the overall performance of the SLM algorithm is greatly improved, which is suitable for the design and application of 5G and future wireless communication systems.

[0092] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for suppressing PAPR of an OFDM system based on HPSO, characterized in that: include, Initialize OFDM system parameters; Generate OFDM symbols; Calculate PAPR and optimize PAPR based on hierarchical particle swarm optimization; The HPSO-based OFDM system PAPR suppression method selects the optimal phase sequence through a hierarchical particle swarm optimization algorithm to reduce the PAPR.

2. The method for suppressing PAPR of an OFDM system based on HPSO according to claim 1, characterized in that: The hierarchical particle swarm optimization algorithm adopts a multi-level structure, including a main layer and a sub-layer, and performs phase sequence optimization in each layer to enhance the PAPR optimization effect.

3. The method for suppressing PAPR of an OFDM system based on HPSO according to claim 2, characterized in that: The main layer manages multiple sublayers, each sublayer contains a number of particles, and the optimization algorithm is executed in parallel in different sublayers to increase the diversity of phase search and global optimization capability.

4. The method for suppressing PAPR of an OFDM system based on HPSO according to claim 2, characterized in that: The main layer updates the global optimal solution of the main layer according to the best result of the sub-layer at the end of each iteration, thereby selecting a phase sequence with the minimum PAPR in a global range.

5. The method for suppressing PAPR of an OFDM system based on HPSO according to claim 2, characterized in that: The particles in the sublayer update their positions through inertia weights, cognitive coefficients and social coefficients to make them move closer to the global optimal and hierarchical optimal phase sequences, further reducing the PAPR.

6. The method for suppressing PAPR of an OFDM system based on HPSO according to claim 1, characterized in that: The final optimization effect of the hierarchical particle swarm optimization method is demonstrated by comparing the CCDF curves, which includes the PAPR performance comparison of no optimization, traditional SLM, PSO-SLM and hierarchical PSO-SLM.

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