A Novel Particle Swarm Optimization for PAPR Reduction of OFDM Systems

Ali Asghar Parandoosh, Javad Taghipour, V. Vakili
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引用次数: 2

Abstract

Orthogonal frequency division multiplexing (OFDM) is usually regarded as a spectral efficient multicarrier modulation technique, yet it suffers from a high peak to average power ratio (PAPR) problem. Partial transmit sequences (PTS) is one of the most well-known schemes to reduce the PAPR in OFDM systems. However, the conventional PTS scheme requires an exhaustive searching over all combinations of allowed phase factors. Consequently, the computational complexity increases exponentially with the number of the sub-blocks. Particle swarm optimization (PSO) algorithm is a recently proposed approach to solve the optimization problem of finding the phase factors of the PTS. In this paper we propose a new method for reducing computational complexity of the original PSO (OPSO) technique. Simulation results show that the proposed PSO (PPSO) compare to the original PSO can effectively reduce the computational complexity of finding phase factors of the PTS.
一种新的粒子群算法降低OFDM系统的PAPR
正交频分复用技术(OFDM)通常被认为是一种频谱高效的多载波调制技术,但其峰值平均功率比(PAPR)较高。部分发送序列(PTS)是OFDM系统中降低PAPR的最著名的方案之一。然而,传统的PTS方案需要对所有允许相位因子的组合进行穷举搜索。因此,计算复杂度随着子块的数量呈指数增长。粒子群优化算法(PSO)是近年来提出的一种求解PTS相位因子的优化方法。本文提出了一种降低原粒子群算法计算复杂度的新方法。仿真结果表明,与原粒子群算法相比,提出的粒子群算法(PPSO)可以有效降低寻找相位因子的计算复杂度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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