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PTS scheme based on MCAKM for peak-to-average power ratio reduction in OFDM systems

机译:基于MCAKM的PTS方案,用于降低OFDM系统中的峰均功率比

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This study considers the application of the partial transmit sequence (PTS) technique to reduce the peak-to-average power ratio (PAPR) in orthogonal frequency division multiplexing (OFDM) systems. The conventional PTS approach has proved its high effectiveness in PAPR reduction for OFDM signals where the reduction performance of PAPR depends mainly on phase rotation factors. Finding the optimal phase rotation factors requires an exhaustive computationally task, which is a serious implementation problem in practical systems. To fix this issue of computational complexity and reduce the PAPR at the same time, in the present work, a novel PTS approach based on multi-population cultural algorithm adopting knowledge migration (MCAKM) has been proposed for optimal phase rotation factors search. Computer simulation results show that the proposed MCAKM-PTS technique leads to a better PAPR reduction and bit error rate performance with a significant reduction in computational complexity compared to the conventional PTS and the previously optimisation algorithms applied to PTS such as particle swarm optimisation, artificial bee colony, and electromagnetism-like algorithm.
机译:本研究考虑了部分发射序列(PTS)技术的应用,以降低正交频分复用(OFDM)系统中的峰均功率比(PAPR)。传统的PTS方法已证明在降低OFDM信号的PAPR方面具有很高的效果,其中PAPR的降低性能主要取决于相位旋转因子。寻找最佳相位旋转因子需要详尽的计算任务,这在实际系统中是一个严重的实现问题。为了解决这一计算复杂性问题并同时降低PAPR,在当前工作中,提出了一种基于多种群文化算法并采用知识迁移(MCAKM)的新型PTS方法,用于最优相位旋转因子搜索。计算机仿真结果表明,与传统的PTS和先前应用于PTS的优化算法(例如粒子群优化,人工蜂)相比,所提出的MCAKM-PTS技术可带来更好的PAPR降低和误码率性能,并显着降低计算复杂度殖民地和类似电磁的算法。

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