基于动态离散粒子群优化的PTS相位系数搜索算法  

PTS Phase Coefficient Search Algorithm Based on Dynamic Discrete Particle Swarm Optimization

作　　者：王沁[1] 李磊[1] 陆成勇[1] 

机构地区：[1]北京科技大学信息工程学院,北京100083

出　　处：《系统仿真学报》2010年第12期2799-2804,共6页Journal of System Simulation

基　　金：国家高技术研究发展计划(863计划)(2008AA01Z134)

摘　　要：部分传输序列(PTS)算法是一种有效的且无畸变的降低正交频分多路复用(OFDM)系统发送信号峰均比的算法,但其实现的时间复杂度较高。为了在不影响降低峰均比性能的前提下,减少算法实现的时间复杂度,提出了一种基于动态离散粒子群优化的PTS相位系数搜索(DDPSO-PTS)算法。该算法利用粒子群优化算法优良的迭代寻优能力,寻找最优的相位系数序列,并且通过动态调整粒子数量,来减少算法的时间复杂度。DDPSO-PTS算法的平均时间复杂度比传统的PTS算法的平均时间复杂度减小了50%到90%。仿真结果分析表明,在相邻、交织和随机分割条件下,相应的DDPSO-PTS算法的性能损失为0到0.4dB。The Partial Transmit Sequence （PTS） is a very promising peak-to-average ratio （PAPR） reduction algorithm for OFDM system since it does not generate any signal distortion.However,its high time complexity makes it difficult for implementation.For reducing the time complexity with neglectable performance penalty,a dynamic discrete particle swarm optimization based PTS （DDPSO-PTS） phase coefficient search algorithm was proposed to implement the PTS approach based on the concept of particle swarm optimization （PSO） algorithm.DDPSO-PTS algorithm seeks the optimum PTS phase coefficients with the best ability of iterative optimization of Particle Swarm Optimization algorithm.The number of particles will be adjusted during iterations to reduce the time complexity.The DDPSO-PTS algorithm can reduce 50% to 90% average time complexity compared with traditional PTS algorithm.The simulations show that with adjacent,interleaved and random partitioning scheme,the performance degradations of DDPSO-PTS algorithm are 0 to 0.4dB.

关 键 词：正交频分多路复用 粒子群优化 峰均比 部分传输序列 

分 类 号：TN919.72[电子电信—通信与信息系统]