Channel Equalization of MIMO-OFDM System Based on Extreme Learning Machine
Ling Yang, Ming Ming Nie, Zi Long Zhong, Bin Bin Xue, Na Lv · Applied Mechanics and Materials · 2014
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.