Channel estimation based on neural network in space time block coded MIMO-OFDM system

Authors:
Muhammet Nuri Seyman;Necmi TaşPıNar
Affiliations:
Department of Electronic Communication, Vocational High School, Kirikkale University, 71450 Kirikkale, Turkey;Department of Electrical and Electronic Engineering, Erciyes University, 38039 Kayseri, Turkey
Venue:
Digital Signal Processing
Year:
2013

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Abstract

In this study, we propose feed-forward multilayered perceptron (MLP) neural network trained with the Levenberg-Marquardt algorithm to estimate channel parameters in MIMO-OFDM systems. Bit error rate (BER) and mean square error (MSE) performances of least square (LS) and least mean square error (LMS) algorithms are also compared to our proposed neural network to evaluate the performances. Neural network channel estimator has got much better performance than LS and LMS algorithms. Furthermore it doesn@?t need channel statistics and sending pilot tones, contrary to classical algorithms.