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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 Transmission Sequence (PTS) algorithm is an efficient and distortion free algorithm to reduce the PAPR of transmitted signals in Orthogonal Frequency Division Multiplexing (OFDM) systems, but its time complexity is high. In order to reduce the time complexity of the algorithm without affecting the performance of reducing PAPR, a PTS phase coefficient search (DDPSO-PTS) algorithm based on dynamic discrete particle swarm optimization is proposed. The algorithm uses the excellent iterative optimization ability of particle swarm optimization algorithm to find the optimal phase coefficient sequence, and reduces the time complexity of the algorithm by dynamically adjusting the number of particles. The average time complexity of DDPSO-PTS algorithm is reduced by 50% to 90% compared with the average time complexity of traditional PTS algorithm. The simulation results show that the performance loss of the corresponding DDPSO-PTS algorithm is 0 to 0.4 dB under the conditions of adjacent, interleaved and randomized partitions.