Recurrent neural network based channel estimation technique for STBC coded MIMO system over Rayleigh fading channel

Authors:
Parismita Gogoi;Kandarpa Kumar Sarma
Affiliations:
Gauhati University, Assam, India;Gauhati University, Assam, India
Venue:
Proceedings of the CUBE International Information Technology Conference
Year:
2012

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Abstract

Artificial Neural Networks (ANN)s, due to their high degree of adaptability, can be used to model nonlinear phenomenon of channel estimation. In this work, a channel estimation technique based on Recurrent Neural Network (RNN) has been proposed as an alternative to pilot based channel estimation technique for STBC- MIMO systems over Rayleigh fading channels. Learning property of ANN is fully exploited for decoding the degraded symbols over severely faded channel. This technique is found to be more bandwidth efficient compared to pilot-based channel estimation techniques. Simulated results in terms of bit error rates (BER) vs. signal to noise ratio (SNR) depict the effectiveness of the learning capability of ANNs for the task of channel estimation over wireless fading channel.