MAC Sub-Layer Analysis with Channel Estimation in Broadband Power Line Communication

• 作者: Mohammad Khaled Andari Seyed Ali Asghar Beheshti
• 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 THROUGHPUT Access DELAY
• 年，卷（期）: 2011,（3）
• 页码范围: 141-148
• 页数: 8页
• 分类号: TN91

摘要

Broadband power line communication (BPLC) gained a lot of interest because of low cost and high performance communication network in access area. In this paper physical (PHY) layer and medium access control (MAC) sub-layer of BPLC are considered. Furthermore, effects of bit error rate (BER) are analyzed in MAC sub-layer. Powerful turbo convolutional code (TCC) and wideband orthogonal frequency division multiplexing (OFDM) are used in PHY layer. Carrier sense multiple access (CSMA) and virtual slot multiple access (VSMA) are taken into consideration in MAC sub-layer. Multilayered perceptrons neural network with backpropagation (BP) learning channel estimator algorithm compare to classic algorithm in for channel estimating. The simulation results show that the proposed neural network estimation decreases bit error rate then in MAC sub-layer throughput increases and access delay is decreased.