电子学报 ›› 2019, Vol. 47 ›› Issue (11): 2407-2412.DOI: 10.3969/j.issn.0372-2112.2019.11.024

• 学术论文 • 上一篇    下一篇

抑制脉冲型噪声的高斯拖尾非线性函数设计

张杨勇1, 罗忠涛2, 聂雅琴1, 张刚2   

  1. 1. 中国船舶重工集团公司第七二二研究所低频电磁通信技术实验室, 湖北武汉 430019;
    2. 重庆邮电大学通信与信息工程学院, 重庆 400065
  • 收稿日期:2018-10-09 修回日期:2019-02-28 出版日期:2019-11-25 发布日期:2019-11-25
  • 通讯作者: 罗忠涛
  • 作者简介:张杨勇 男,1983年出生于湖北省.2009年毕业于中国舰船研究院.高级工程师.主要研究方向为通信与信号处理.E-mail:medy99@126.com;聂雅琴 女,1993年出生于湖北省.2011年毕业于武汉大学电子信息学院.主要研究方向为通信体制算法和嵌入式软件设计.E-mail:nieyq2005@126.com;张刚 男,1976年出生于四川省.现为重庆邮电大学通信与信息工程学院教授.主要研究方向为混沌通信与微弱信号检测.E-mail:zhanggang@cqupt.edu.cn
  • 基金资助:
    国家自然科学基金(No.61701067,No.61771085,No.61671095);重庆市教育委员会科研基金(No.KJ1600427,No.KJ1600429)

Optimal Design of the Gaussian-Tailed Zero Memory Nonlinearity Function for Impulsive Noise Suppression

ZHANG Yang-yong1, LUO Zhong-tao2, NIE Ya-qin1, ZHANG Gang2   

  1. 1. Laboratory of Low-frequency Electro-magnetic Communication Technology with the 722 Research Institute, CSIC, Wuhan, Hubei 430019, China;
    2. School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
  • Received:2018-10-09 Revised:2019-02-28 Online:2019-11-25 Published:2019-11-25

摘要: 低频通信中脉冲型噪声会严重降低通信性能.针对脉冲型噪声的抑制问题,本文提出高斯拖尾零记忆非线性(Gaussian-tailed Zero Memory Nonlinearity,GZMNL)函数的最优化设计方法.GZMNL函数含有两个参数,分别控制其线性范围和拖尾程度,故适用于多种噪声分布.本文提出GZMNL设计以效能最大化为优化目标,采用自适应搜索算法来寻找GZMNL参数的最佳值.然后讨论了GZMNL在SαS(Symmetric α-Stable,SαS)噪声分布下的快速设计方法,以及在未知噪声分布时的稳健设计方法.最后,仿真SαS噪声和实测大气噪声数据的处理结果表明:本文设计方法在检测性能上能够接近最优非线性,且能够有效抑制未知分布的噪声.

关键词: 脉冲型噪声, 非线性变换, 高斯拖尾零记忆非线性, 效能函数, 非线性优化

Abstract: Impulsive noise can greatly degrade the performance of long wave communications.This paper proposes the optimal design of the Gaussian-tailed zero memory nonlinearity (GZMNL) function to suppress impulsive noise.The GZMNL function which was proposed for the symmetric α-stable (SαS) noise is not robust in applications,because of the lack of adaptive parameters.This paper proposes to design the GZMNL parameters adaptively to control the linear range and the tails,so that the GZMNL can be effective for various noise distributions.In the GZMNL design,the efficiency is employed as the objective function which is maximized over the GZMNL parameters.To solve this optimization problem,we develop a derivative-free optimization algorithm which searches the maximum efficacy adaptively.Considering practical applications,we propose two fast algorithms for the GZMNL design in the SαS noise,as well as a robust method for the GZMNL design in unknown noise distributions.Simulation results based on the SαS noise and real atmospheric noise show that the GZMNL design achieves almost the best nonlinearity in known noise distributions.The GZMNL design is effective and robust for unknown noise distributions.

Key words: impulsive noise, nonlinear transformation, GZMNL, efficiency function, nonlinear optimization

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