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

被引:51
作者
Seyman, Muhammet Nuri [1 ]
Taspinar, Necmi [2 ]
机构
[1] Kirikkale Univ, Vocat High Sch, Dept Elect Commun, TR-71450 Kirikkale, Turkey
[2] Erciyes Univ, Dept Elect & Elect Engn, TR-38039 Kayseri, Turkey
关键词
MIMO-OFDM; Feed-forward neural network; Channel impulse response (CIR); Levenberg-Marquardt algorithm; DESIGN;
D O I
10.1016/j.dsp.2012.08.003
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
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. Crown Copyright (C) 2012 Published by Elsevier Inc. All rights reserved.
引用
收藏
页码:275 / 280
页数:6
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