计算机与现代化 ›› 2021, Vol. 0 ›› Issue (02): 89-93.

• 网络与通信 • 上一篇    下一篇

一种联合盲均衡算法

  

  1. (1.中国电子科技集团公司第三十二研究所IC产品部,上海201808;2.大连理工大学微电子学院,辽宁大连116024)
  • 出版日期:2021-03-01 发布日期:2021-03-01
  • 作者简介:谭晓刚(1996—),男(土家族),贵州印江人,硕士研究生,研究方向:混合信号集成电路设计,E-mail: 794354126@qq.com; 戴天喆(1988—),男,硕士,研究方向:信息与通信处理,E-mail: daitianzhe@126.com; 董树林(1995—),男,硕士研究生,研究方向:数模混合集成电路设计,E-mail: dsl1121@mail.ustc.edu.cn; 张艺鉴(1998—),男,本科生,E-mail: master0502@mail.dlut.edu.cn; 任敏华(1975—),男,研究员,研究方向:集成电路设计,E-mail: renminhua@139.com。

An Algorithm of Joint Blind Equalization

  1. (1. Department of IC Product, 32nd Research Institute of China Electronics Technology Group Corporation, 
    Shanghai 201808, China; 2. School of Microelectronics, Dalian University of Technology, Dalian 116024, China)

  • Online:2021-03-01 Published:2021-03-01

摘要: 为克服数字基带信号在通过非屏蔽五类双绞线时产生的严重码间干扰(ISI),常采用自适应均衡技术来减小码间干扰,大大降低接收端信号的误码率。最小均方误差(LMS)算法能有效降低码间干扰,但需要训练序列,因此影响传输效率。基于判决引导的最小均方误差(DDLMS)算法不需要训练序列,但在眼图未睁开的情况下,可能出现误判,甚至引起误收敛。恒模算法(CMA)具有比DDLMS算法更好的盲均衡特性,但是剩余误差较大。本文提出一种新颖的联合盲均衡算法,即优化现有的CMA算法,与DDLMS算法组成新的联合盲均衡算法,利用均方误差(MSE)来控制2种算法的权值。MATLAB建模和仿真结果表明,新的联合盲均衡算法克服了CMA算法剩余误差较大和DDLMS算法误收敛的缺陷,且能有效对非屏蔽五类双绞线中传输的数字信号进行均衡。

关键词: 数字基带信号, 码间干扰; 最小均方误差算法; 判决引导; 恒模算法; 盲均衡

Abstract: In order to overcome the severe Inter-Symbol Interference (ISI) effect generated by digital baseband signals passing through UTP-CAT5, adaptive equalization technology is widely used to reduce the Inter-Symbol Interference, which greatly reduces the bit error rate of the received signal. The Least Mean Square (LMS) algorithm can effectively reduce Inter-Symbol Interference, but requires training sequences, which affects transmission efficiency. The Decision-Directed LMS (DDLMS) algorithm does not require training sequences, but when the eye diagram is not open, misjudgment may occur and even cause false convergence. The Constant Modulus Algorithm (CMA) has better blind equalization characteristics than the DDLMS algorithm, but the residual error is large. A novel joint blind equalization algorithm is proposed, which optimizes the existing CMA algorithm, and forms a new joint blind equalization algorithm with the DDLMS algorithm, and uses the Mean Square Error (MSE) to control the weights of the two algorithms. MATLAB modeling and simulation results show that the new joint blind equalization algorithm overcomes the shortcomings of the large residual error of the CMA algorithm and the false convergence of the DDLMS algorithm, and can effectively equalize the digital signals transmitted in the UTP-CAT5.

Key words: digital baseband signal, Inter-Symbol Interference (ISI), Least Mean Square (LMS) algorithm, decision-directed, Constant Modulus Algorithm (CMA), blind equalization