适用于稀疏多径信道的稀疏自适应常模盲均衡算法

马思扬; 彭华; 王彬

doi:10.11959/j.issn.1000-436x.2017017

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适用于稀疏多径信道的稀疏自适应常模盲均衡算法

学术通信 | 更新时间：2024-06-05

- 适用于稀疏多径信道的稀疏自适应常模盲均衡算法
- Sparse adaptive constant blind equalization algorithm for sparse multipath channel
- 通信学报 2017年38卷第1期页码：149-157
- 作者机构：
  
  解放军信息工程大学，河南郑州 450001
- 作者简介：
  
  [ "马思扬（1991-），女，浙江金华人，解放军信息工程大学硕士生，主要研究方向为通信信号处理、稀疏多径信道均衡。" ]
  [ "彭华（1973-），男，江西萍乡人，博士，解放军信息工程大学教授、博士生导师，主要研究方向为通信信号处理、软件无线电。" ]
  [ "王彬（1971-），女，河南郑州人，博士，解放军信息工程大学副教授、硕士生导师，主要研究方向为通信信号处理、信道均衡与辨识。" ]
- 基金信息：
  
  国家自然科学基金资助项目(61401511)
- DOI：10.11959/j.issn.1000-436x.2017017
  中图分类号： TN911.5
- 网络出版日期：2017-01，
  
  纸质出版日期：2017-01-25
- 稿件说明：
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马思扬, 彭华, 王彬. 适用于稀疏多径信道的稀疏自适应常模盲均衡算法[J]. 通信学报, 2017,38(1):149-157.

Si-yang MA, Hua PENG, Bin WANG. Sparse adaptive constant blind equalization algorithm for sparse multipath channel[J]. Journal on communications, 2017, 38(1): 149-157.
马思扬, 彭华, 王彬. 适用于稀疏多径信道的稀疏自适应常模盲均衡算法[J]. 通信学报, 2017,38(1):149-157. DOI： 10.11959/j.issn.1000-436x.2017017.

Si-yang MA, Hua PENG, Bin WANG. Sparse adaptive constant blind equalization algorithm for sparse multipath channel[J]. Journal on communications, 2017, 38(1): 149-157. DOI： 10.11959/j.issn.1000-436x.2017017.

摘要

为了提高稀疏多径信道盲均衡器的收敛速度，提出了一种适用于多进制相移键控（MPSK

M-order phase-shift keying）信号的l

-范数约束的比例系数归一化最小均方常模盲均衡算法。该算法首先利用信号的常模特性和均衡器抽头系数的稀疏性，构造出基于l

-范数约束的稀疏常模盲均衡代价函数，然后依据梯度下降法推导出均衡器抽头系数更新公式，并对迭代步长进行归一化和比例系数化。算法为每个抽头系数分配与其当前时刻的幅度成正比的步长参数，并自适应地对幅度极小系数做向零收缩微调。理论分析和仿真实验表明，与现有稀疏多径信道盲均衡算法相比，该算法在保持较低剩余符号间干扰的同时，能有效提高均衡器的收敛速度。

Abstract

In order to

improve the convergence rate of the blind equalizer for sparse multipath channel

a novel blind equalization approach called l

-norm constraint proportionate normalized least mean square constant algorithm was proposed for M-order phase-shift keying (MPSK) signal.Based on the constant modulus characteristics of MPSK signal and the sparse property of equalizer

a new blind equalization cost function with the l

-norm penalty on the equalizer tap coefficients was firstly constructed.Then the update formula of the tap coefficients was derived according to the gradient descent algorithm.Moreover

the iteration step was updated by drawing upon the normalized proportionate factor.The algorithm not only assigned step sizes proportionate to the magnitude of the current individual tap weights

but also attracted the inactive taps to zero adaptively.Theoretical analysis and simulation results show that the proposed algorithm outperforms the existing blind equalization algorithms for sparse channel in reducing ISI and improving convergence rate.

关键词

Keywords

references

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