Comparative Performance Analysis of ANN Implemented LMS with ANN for Channel Estimation in AWGN Channel Scenario
Probal Banerjee1, Pallab Banerjee2, Shweta Sonali Dhal3
1Probal Banerjee, Lecturer, ECE Department, Cambridge Institute of Technology, Ranchi.
2Pallab Banerjee, Lecturer, CSE Department, Cambridge Institute of Technology, Ranchi.
3Shweta Sonali Dhal, Lecturer, EEE Department, Cambridge Institute of Technology, Ranchi.
Manuscript received on August 01, 2012. | Revised Manuscript received on August 05, 2012. | Manuscript published on August 10, 2012. | PP: 1-4 | Volume-1 Issue-3, August 2012. | Retrieval Number: B0196071312/2012©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In this paper we have done channel estimation using the concepts of LMS algorithm, after that we have implemented the logic of LMS algorithm using the concepts of Supervised Artificial Neural Network and then we have performed channel estimation directly applying the concepts of Supervised Artificial Neural Network. Finally we have compared the performances (BER v/s SNR and Throughput v/s SNR) of these three methods for channel estimation under AWGN channel scenario. Matlab (version 7.9) is used here as the simulation platform.
Keywords: Channel estimation, LMS, Artificial Neural Network, BER, Throughput