Pilot Based Channel Estimation in Broadband Power Line Communication Networks

• 作者: A. A. Beheshti M. Kh. Andari
• 来源期刊: 通讯与网络(英文)
• 学科: 工学
• 关键词: BPLC BACK-PROPAGATION NEURAL Network (BPNN) CHANNEL Estimation PILOT THROUGHPUT
• 年，卷（期）: 2012,（3）
• 页码范围: 240-247
• 页数: 8页
• 分类号: TN91

摘要

In this paper pilot based channel estimation is being considered for broadband power line communication (BPLC) networks witch used orthogonal frequency division multiplexing (OFDM) in order to transmit high rate data. To estimate channel in time or frequency some pilot must be used. Number of these pilots and deployment of them is very important for proper estimation in different channel with varying time and frequency. Carrier sense multiple access (CSMA) and hybrid multiple access protocol are taken into consideration in MAC sub-layer. Multilayered perceptions neural network with backpropagation (BP) learning channel estimator algorithm with different pilot deployment compare to classic algorithm in for channel estimating. Simulation results show the proposed neural network estimation decreases bit error rate and therefore network throughput increases.