基于改进离散粒子群的OFDM系统峰均比抑制

部分传输序列(PTS)是抑制正交频分复用系统峰均比的有效方法之一,但该算法需要进行最佳相位因子的全遍历搜索,存在计算复杂度偏高的问题.因此针对这一问题,本文提出一种基于离散粒子群优化PTS的峰均比抑制算法.所提算法首先定义了一种新的确定惯性权重的方法,然后引入变异算子对原始速度更新公式进行改进,解决了传统离散粒子群算法易于早熟,往往很难收敛到全局最优的缺陷.仿真结果表明,本文所提算法能获得优于传统DPSO算法0.3 dB左右的PAPR性能,且计算复杂度低于传统PTS算法.

PAPR Suppression in OFDM System Based on Improved Discrete Particle Swarm Optimization

Partial Transmission Sequence (PTS) is one of the effective methods to suppress the Peak to Average Power Ratio (PAPR) in Orthogonal Frequency Division Multiplexing (OFDM) systems. However, the algorithm needs a full traversal search for the best phase factor, resulting in great computational complexity. Therefore, this study proposes a PAPR suppression algorithm based on Discrete Particle Swarm Optimization (DPSO). Firstly, a new method for determining inertia weight is defined. Then the mutation operator is introduced to improve the original velocity update formula, which enhance the traditional DPSO algorithm that is easy to be premature and difficult to converge to the global optimal. The simulation results reveal that the PAPR performance of the proposed algorithm is better than that of the traditional DPSO algorithm by about 0.3 dB, and the computational complexity is lower than that of the traditional PTS algorithm.