中国邮电高校学报(英文) ›› 2014, Vol. 21 ›› Issue (5): 24-30.doi: 10.1016/S1005-8885(14)60326-5

• Wireless • 上一篇    下一篇

Particle filtering based channel estimation in OFDM power line communication

张培玲1,张洪欣1,刘鸿达1,张玉静1,贺鹏飞2,PANG Xue-li   

  1. 1. 北京邮电大学电子工程学院
    2. 烟台大学光电信息学院
    3. 河南理工大学 
  • 收稿日期:2013-11-28 修回日期:2014-05-13 出版日期:2014-10-31 发布日期:2014-10-30
  • 通讯作者: 张培玲 E-mail:plzhang@hpu.edu.cn
  • 基金资助:

    国家自然科学基金;国家自然科学基金;北京市自然科学基金;河南省控制工程开放实验室开放课题

Particle filtering based channel estimation in OFDM power line communication

  • Received:2013-11-28 Revised:2014-05-13 Online:2014-10-31 Published:2014-10-30
  • Contact: Pei-Ling Zhang E-mail:plzhang@hpu.edu.cn

摘要:

Particle filtering (PF) algorithm has the powerful potential for coping with difficult non-linear and non-Gaussian problems. Aiming at non-linear, non-Gaussian and time-varying characteristics of power line channel, a time-varying channel estimation scheme combined PF algorithm with decision feedback method is proposed. In the proposed scheme, firstly the indoor power line channel is measured using the pseudo-noise (PN) correlation method, and a first-order dynamic autoregressive (AR) model is set up to describe the measured channel, then, the channel states are estimated dynamically from the received signals by exploiting the proposed scheme. Meanwhile, due to the complex noise distribution of power line channel, the performance of channel estimation based on the proposed scheme under the Middleton class A impulsive noise environment is analyzed. Comparisons are made with the channel estimation scheme respectively based on least square (LS), Kalman filtering (KF) and the proposed algorithm. Simulation indicates that PF algorithm dealing with this power line channel estimation difficult non-linear and non-Gaussian problems performance is superior to those of LS and KF respectively, so the proposed scheme achieves higher estimation accuracy. Therefore, it is confirmed that PF algorithm has its own unique advantage for power line channel estimation.

关键词:

power line communication ( PLC), orthogonal frequency division multiplexing (OFDM) , channel estimation, PF, KF

Abstract:

Particle filtering (PF) algorithm has the powerful potential for coping with difficult non-linear and non-Gaussian problems. Aiming at non-linear, non-Gaussian and time-varying characteristics of power line channel, a time-varying channel estimation scheme combined PF algorithm with decision feedback method is proposed. In the proposed scheme, firstly the indoor power line channel is measured using the pseudo-noise (PN) correlation method, and a first-order dynamic autoregressive (AR) model is set up to describe the measured channel, then, the channel states are estimated dynamically from the received signals by exploiting the proposed scheme. Meanwhile, due to the complex noise distribution of power line channel, the performance of channel estimation based on the proposed scheme under the Middleton class A impulsive noise environment is analyzed. Comparisons are made with the channel estimation scheme respectively based on least square (LS), Kalman filtering (KF) and the proposed algorithm. Simulation indicates that PF algorithm dealing with this power line channel estimation difficult non-linear and non-Gaussian problems performance is superior to those of LS and KF respectively, so the proposed scheme achieves higher estimation accuracy. Therefore, it is confirmed that PF algorithm has its own unique advantage for power line channel estimation.

Key words:

power line communication ( PLC), orthogonal frequency division multiplexing (OFDM) , channel estimation, PF, KF

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