OFDM系统的信道与脉冲噪声的联合估计方法

doi:10.11959/j.issn.1000-436x.2018047

通信学报 ›› 2018, Vol. 39 ›› Issue (3): 191-198.doi: 10.11959/j.issn.1000-436x.2018047

• 论文Ⅱ：学术论文 • 上一篇

OFDM系统的信道与脉冲噪声的联合估计方法

吕新荣^1,²,李有明¹,余明宸¹

¹ 宁波大学信息科学与工程学院，浙江宁波 315211
² 浙江工商职业技术学院智能电子学院，浙江宁波 315012

修回日期:2018-02-06 出版日期:2018-03-01 发布日期:2018-04-02
作者简介:吕新荣（1976-），男，浙江永康人，宁波大学博士生，主要研究方向为无线通信技术、电力线通信、稀疏信号处理。|李有明（1963-），男，陕西扶风人，博士，宁波大学教授，主要研究方向为无线宽带通信、电力线通信、协作中继、认知无线电等。|余明宸（1991-），男，河南洛阳人，宁波大学硕士生，主要研究方向为电力线通信技术。
基金资助:
国家自然科学基金资助项目(61571250);宁波市自然科学基金资助项目(2015A610121)

Joint channel and impulsive noise estimation method for OFDM systems

Xinrong LYU^1,²,Youming LI¹,Mingchen YU¹

¹ Faculty of Information Science and Engineering,Ningbo University,Ningbo 315211,China
² School of Intelligent Electronics,Zhejiang Business ＆Technology Institute,Ningbo 315012,China

Revised:2018-02-06 Online:2018-03-01 Published:2018-04-02
Supported by:
The National Natural Science Foundation of China(61571250);The Natural Science Foundation of Ningbo(2015A610121)

摘要/Abstract

摘要：

针对 OFDM 系统中的脉冲噪声问题，提出一种基于压缩感知技术的脉冲噪声抑制方法。该方法将信道脉冲响应和脉冲噪声联合视作一个稀疏向量，将发射数据符号视作未知参数，利用稀疏贝叶斯学习理论联合估计信道、脉冲噪声和数据符号。与现有脉冲噪声抑制方法相比，该方法不仅能够充分利用全部子载波信息，而且不需要信道和脉冲噪声的先验统计信息。仿真结果表明，所提方法在信道估计及误比特率性能上有明显改善。

关键词: 正交频分复用, 信道估计, 脉冲噪声, 稀疏贝叶斯学习, 压缩感知

Abstract:

Aiming at the impulsive noise occurring in OFDM systems,an impulsive noise mitigation algorithm based on compressed sensing theory was proposed.The proposed algorithm firstly treated the channel impulse response and the impulsive noise as a joint sparse vector by exploiting the sparsity of both them.Then the sparse Bayesian learning framework was adopted to jointly estimate the channel impulse response,the impulsive noise and the data symbols,in which the data symbols were regarded as unknown parameters.Compared with the existing impulsive noise mitigation methods,the proposed algorithm not only utilized all subcarriers but also did not use any a priori information of the channel and impulsive noise.The simulation results show that the proposed algorithm achieves significant improvement on the channel estimation and bit error rate performance.

Key words: orthogonal frequency division multiplexing, channel estimation, impulsive noise, sparse Bayesian learning, compressed sensing

中图分类号:

TN911.4

吕新荣,李有明,余明宸. OFDM系统的信道与脉冲噪声的联合估计方法[J]. 通信学报, 2018, 39(3): 191-198.

Xinrong LYU,Youming LI,Mingchen YU. Joint channel and impulsive noise estimation method for OFDM systems[J]. Journal on Communications, 2018, 39(3): 191-198.

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参考文献 22

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参数名称	参数值
系统子带带宽	15 kHz
OFDM符号持续时间	83.3 μs（保护间隔为16.67 μs）
总子载波数N	256
循环前缀长度	64
导频子载波数P	分别为24、44、64
空子载波数U	分别为20、50、80、100
信道长度L	64
信号调制模式	4-QAM
GMM模型	k=3，p_k={0.9,0.07,0.03}，γ_k={1,100,1 000}

OFDM系统的信道与脉冲噪声的联合估计方法

Joint channel and impulsive noise estimation method for OFDM systems

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