一种基于混沌生物地理优化的新型部分序列技术,用于PAPR,减少泛化频率划分,复杂化波形
Xingsi Xue1, SatheeshKumar Palanisamy2, Manikandan A3
1Fujian Provincial Key Laboratory of Big Data Mining and Applications, Fujian University of Technology, China.
Heliyon
|September 8, 2023
概括
本研究介绍了部分传输序列 (PTS) 的混沌生物地理基础优化 (CBBO) 算法,以减少一般化频率分割多重复合 (GFDM) 系统中高峰至平均功率比率 (PAPR).
科学领域:
- 电气工程 电气工程
- 信号处理 信号处理
- 电信 电信服务 电信服务 电信服务
背景情况:
- 高峰到平均功率比 (PAPR) 是对正角频率分割多重复合 (OFDM) 和通用频率分割多重复合 (GFDM) 系统的一个重大挑战.
- 降低PAPR对于提高系统效率和性能至关重要,尤其是在大量数据负载下.
- 部分传输序列 (PTS) 是减少PAPR的有效技术.
研究的目的:
- 开发一种高效的部分传输序列 (PTS) 方法,基于混乱生物地理基于优化 (CBBO) 算法.
- 解决和显著降低通用频率分割多重复合 (GFDM) 波形中的高PAPR问题.
- 为了利用赫米特对称性质来获取实值时间域信号.
主要方法:
- 拟议的方法使用混乱生物地理基础优化 (CBBO) 算法来优化PTS中的相旋转因子组合.
- 赫米蒂安对称性被用来确保一个实值的时间域信号.
- 实施了一种新的混合优化方法,以实现高效和最佳的相位旋转因子选择.
主要成果:
- 与传统的GFDM和OFDM-PTS方法相比,CBBO-PTS技术在最小化PAPR方面表现出卓越的性能.
- 混合优化方法提供快速融合和最小的复杂性.
- 实验结果验证了由拟议的CBBO-PTS方法实现的显著PAPR降低.
结论:
- 开发的CBBO-PTS技术在降低GFDM系统的PAPR方面非常有效.
- 拟议的方法在融合速度和计算复杂性方面比传统技术具有优势.
- 这项研究为现代通信系统中PAPR缓解提供了一种新且高效的解决方案.
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