基于改进的粒子群算法抑制OFDM的峰均比

An improved particle swarm optimization algorithm to suppress the peak to average ratio of OFDM

针对电力线系统中OFDM(Orthogonal Frequency Division Multiplexing)信号高峰均比的问题,提出了一种改进的粒子群算法。该算法在搜索部分传输序列法的相位因子时将位置更新周期分为两个步骤,第一步粒子的位置受上一次扭曲信息的补偿后搜索位置;第二步获知其他粒子的位置以及适应度函数值,利用扭曲函数获得扭曲信息。算法按此周期进行搜索使其快速收敛。仿真结果表明,此算法与基于种群分类与动态学习因子的粒子群算法相比,搜索的复杂度能有效的降低。

An improved particle swarm optimization algorithm is proposed to solve the problem that the partial transmission sequence method suppresses the peak-t〇 -average ratio of OFDM （orthogonal frequency division mu lt ip le x in g ） signal in power line system. The algorithm divides the position update cycle into two steps when searching fo r the phase factor of the partial transmission sequence method. The f irs t step of the particle is affected by the last distorted information , and the second step is to know the location of the other particles and the fitness function value. The distorted function is used to obtain distorted information and the algorithm searches for rapid convergence in this way. Simulation results show that compared w ith the existing particle swarm algor ithm , this algorithm can reduce both the peak power ratio and the complexity of the search effectively.