利用创新的差分进化算法降低OFDM的PAPR

Shu-Hong Lee, Ho-Lung Hung
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引用次数: 2

摘要

为了降低正交频分复用(OFDM)信号的峰均功率比,提出了基于差分进化算法(DE)的注音算法(TI)。TI是一种无失真的PAPR减少技术,但其寻找最优TI方案的搜索复杂度很高,需要对扩展星座的所有可能排列组合进行穷举搜索,这是实际应用中的一个潜在问题。在这项工作中,我们提出了一种新的凸优化方法,以数值确定基于微分进化算法(DETI)的近最优音调注入(TI)解决方案。将DETI与不同的TI方案进行了PAPR降低和搜索复杂度性能的比较。仿真结果表明,该方法具有良好的PAPR降低和误码率(BER)性能。最后,DETI算法不仅显著降低了PAPR,而且降低了计算复杂度。仿真结果表明,该方法与穷举搜索的PAPR降低效果基本一致。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using Innovative Differential Evolution Algorithm for OFDM Reducing PAPR
In this paper, tone injection (TI) based on differential evolution algorithm (DE) is proposed to reduce the peak-to-average power ratio (PAPR) of orthogonal frequency division multiplexing (OFDM) signals. TI is a distortionless PAPR reduction technique, but its high search complexity for finding optimal TI scheme requires an exhaustive search over all combinations of possible permutations of the expanded constellation, which is a potential problem for practical applications. In this work we present a novel convex optimization approach to numerically determine the near-optimal tone injection (TI) solution based on a differential evolution algorithm (DETI). DETI is compared to different TI schemes for PAPR reduction and search complexity performances. The simulation results show that the proposed DETI method provides good PAPR reduction and bit error-rate (BER) performances. Finally, the DETI algorithm not only reduces the PAPR significantly, but also decreases the computational complexity. The simulation results show that it achieves more or less the same PAPR reduction as that of exhaustive search.
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