T. Necmi and S. M. Nuri, “Back Propagation Neural Network Approach for Channel Estimation in OFDM System, Wireless Communications, Networking and Information Security (WCNIS),” 2010 IEEE International Conference, Anchorage, 3-8 May 2010, pp. 265-268.

has been cited by the following article:

• TITLE: Pilot Based Channel Estimation in Broadband Power Line Communication Networks

  AUTHORS: M. Kh. Andari, A. A. Beheshti

  KEYWORDS: BPLC; Back-Propagation Neural Network (BPNN); Channel Estimation; Pilot; Throughput

  JOURNAL NAME: Communications and Network, Vol.4 No.3, August 31, 2012

  ABSTRACT: 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.