Channel Equalization of MIMO-OFDM System Based on Extreme Learning Machine

Abstract:

This paper proposes a novel and efficient method for channel equalization of MIMO-OFDM system. The method utilizes extreme learning machine (ELM), a class of supervised learning algorithms, to achieve fast training and low bit error rates. The numerical simulation results show that the proposed methods significantly outperform traditional feed-forward neural networks based MIMO-OFDM system equalizers in terms of bit error rate performance.

• Periodical: Applied Mechanics and Materials (Volumes 536-537)
• Pages: 1751-1757
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.536-537.1751
• Online since: April 2014
• Authors: Ling Yang*, Ming Ming Nie, Zi Long Zhong, Bin Bin Xue, Na Lv
• Keywords: Channel Equalization, Extreme Learning Machine, MIMO-OFDM

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