系统工程与电子技术 ›› 2026, Vol. 48 ›› Issue (10): 3654-3661.doi: 10.12305/j.issn.1001-506X.2026.10.35

• 通信与网络 • 上一篇    

正交多载波扩频体制下的峰均比抑制联合算法

李德瑞1,2,3(), 王巍1,3, 于学洋1,2,3, 李淑秋1,3, 李宇1,2,3, 田亚男1,3   

  1. 1. 中国科学院声学研究所,北京 100190
    2. 中国科学院大学,北京 100049
    3. 中国科学院先进水下信息技术重点实验室,北京 100190
  • 收稿日期:2025-09-02 出版日期:2026-10-25 发布日期:2026-09-30
  • 通讯作者: 李宇 E-mail:liderui21@mails.ucas.ac.cn
  • 作者简介:李德瑞(1998—),男,博士研究生,主要研究方向为水声信号处理
    王 巍(1983—),男,研究员,博士,主要研究方向为水声信号处理
    于学洋(1998—),男,助理研究员,博士,主要研究方向为水声信号处理
    李淑秋(1963—),女,研究员,博士,主要研究方向为水声信号处理
    田亚男(1995—),女,助理研究员,博士,主要研究方向为水声信号处理
  • 基金资助:
    国家自然科学基金(62401559)资助课题

Joint algorithm for peak to average power ratio reduction in orthogonal multi-carrier spread spectrum systems

Derui Li1,2,3(), Wei Wang1,3, Xueyang Yu1,2,3, Shuqiu Li1,3, Yu Li1,2,3, Ya’nan Tian1,3   

  1. 1. Institute of Acoustics,Chinese Academy of Sciences,Beijing 100190,China
    2. University of Chinese Academy of Sciences,Beijing 100049,China
    3. Key Laboratory of Science and Technology on Advanced Underwater Acoustic Signal Processing,Chinese Academy of Sciences,Beijing 100190,China
  • Received:2025-09-02 Online:2026-10-25 Published:2026-09-30
  • Contact: Yu Li E-mail:liderui21@mails.ucas.ac.cn

摘要:

针对正交多载波扩频系统的高峰均功率比(peak to average power ratio, PAPR)问题,提出一种基于选择映射(selected mapping, SLM)与部分传输序列(partial transmit sequence, PTS)的联合优化算法。该方法首先通过SLM算法对扩频码组进行初步PAPR抑制,随后在码片维度实施改进动态离散粒子群优化的PTS(improved dynamic discrete particle swarm optimization-PTS, IDDPSO-PTS)算法进行二次优化。IDDPSO-PTS算法添加动态调整变异权重的变异项并通过离散-连续两步迭代相位优化机制,突破传统离散相位空间限制。从仿真结果可以看出,与现有基于离散粒子群算法的PTS(discrete particle swarm optimization-PTS, DPSO-PTS)方法相比,所提算法无需边带信息,在互补累积分布函数为10−3时分别获得3.1 dB和1.3 dB的PAPR性能增益。

关键词: 正交频分复用, 扩频, 峰均比抑制, 选择映射, 部分传输序列

Abstract:

To address the high peaktoaverage power ratio (PAPR) problem in orthogonal multi-carrier spread spectrum systems, a joint optimization algorithm based on selected mapping (SLM) and partial transmit sequence (PTS) is proposed. The method first performs preliminary PAPR suppression on the spreading code set via the SLM algorithm, followed by a secondary optimization in the chip dimension using an improved dynamic discrete particle swarm optimization-PTS (IDDPSO-PTS) algorithm. The IDDPSO-PTS algorithm dynamically adjusts mutation factors and employs a two-step discrete-continuous iterative phase optimization mechanism to break through the limitations of traditional discrete phase spaces. Simulation results demonstrate that, compared to existing discrete particle swarm optimization-PTS (DPSO-PTS) methods, the proposed algorithm requires no side information and achieves PAPR performance gains of 3.1 dB and 1.3 dB, respectively, at a complementary cumulative distribution function of 10−3.

Key words: orthogonal frequency division multiplexing, spread spectrum, peaktoaverage power ratio (PAPR) reduction, selected mapping (SLM), partial transmit sequence (PTS)

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