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首页> 外文期刊>Eurasip Journal on Wireless Communications and Networking >A Suboptimal PTS Algorithm Based on Particle Swarm Optimization Technique for PAPR Reduction in OFDM Systems
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A Suboptimal PTS Algorithm Based on Particle Swarm Optimization Technique for PAPR Reduction in OFDM Systems

机译:基于粒子群优化技术的次优PTS算法在OFDM系统中降低PAPR

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摘要

A suboptimal partial transmit sequence (PTS) based on particle swarm optimization (PSO) algorithm is presented for the low computation complexity and the reduction of the peak-to-average power ratio (PAPR) of an orthogonal frequency division multiplexing (OFDM) system. In general, PTS technique can improve the PAPR statistics of an OFDM system. However, it will come with an exhaustive search over all combinations of allowed phase weighting factors and the search complexity increasing exponentially with the number of subblocks. In this paper, we work around potentially computational intractability; the proposed PSO scheme exploits heuristics to search the optimal combination of phase factors with low complexity. Simulation results show that the new technique can effectively reduce the computation complexity and PAPR reduction.
机译:提出了一种基于粒子群优化(PSO)算法的次优部分发射序列(PTS),以降低计算复杂度并降低正交频分复用(OFDM)系统的峰均功率比(PAPR)。通常,PTS技术可以改善OFDM系统的PAPR统计信息。然而,它将伴随着对允许的相位加权因子的所有组合的详尽搜索,并且搜索复杂度随着子块的数量呈指数增长。在本文中,我们解决了潜在的计算难点。提出的PSO方案利用启发式算法来搜索具有低复杂度的相位因子的最佳组合。仿真结果表明,该新技术可以有效降低计算复杂度和降低PAPR。

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