A Design of Extreme Learning Machine Based Receiver for 2×2 MIMO-OFDM System

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.

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Semi-blind Channel Estimation of MIMO-OFDM System Based on Extreme Learning Machine

2013 Sixth International Symposium on Computational Intelligence and Design ◽

10.1109/iscid.2013.155 ◽

2013 ◽

Cited By ~ 1

Author(s):

Ling Yang ◽

Binbin Xue ◽

Mingming Nie ◽

Changnian Liu ◽

Qiang Zhang

Keyword(s):

Channel Estimation ◽

Extreme Learning Machine ◽

Blind Channel Estimation ◽

Ofdm System ◽

Blind Channel ◽

Mimo Ofdm ◽

Learning Machine

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Signal detection of MIMO-OFDM system based on auto encoder and extreme learning machine

2017 International Joint Conference on Neural Networks (IJCNN) ◽

10.1109/ijcnn.2017.7966042 ◽

2017 ◽

Cited By ~ 19

Author(s):

Xin Yan ◽

Fei Long ◽

Jingshuai Wang ◽

Na Fu ◽

Weihua Ou ◽

...

Keyword(s):

Signal Detection ◽

Extreme Learning Machine ◽

Ofdm System ◽

Mimo Ofdm ◽

Learning Machine

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Energy efficient equalizer design for MIMO OFDM communication systems using improved split complex extreme learning machine

Signal Image and Video Processing ◽

10.1007/s11760-021-01933-2 ◽

2021 ◽

Author(s):

Swetaleena Sahoo ◽

Harish Kumar Sahoo ◽

Sarita Nanda

Keyword(s):

Extreme Learning Machine ◽

Energy Efficient ◽

Communication Systems ◽

Mimo Ofdm ◽

Learning Machine

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A Portable Integrated Ship Monitoring Command System

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.536-537.824 ◽

2014 ◽

Vol 536-537 ◽

pp. 824-827

Author(s):

Ming Liu ◽

Huan Zhang

Keyword(s):

Channel Equalization ◽

Error Rates ◽

Rate Performance ◽

Ofdm System ◽

Fast Training ◽

Supervised Learning Algorithms ◽

Mimo Ofdm ◽

Feed Forward Neural Networks ◽

Simulation Results ◽

Learning Machine

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.

Download Full-text