文章基本信息

标题：Artificial Neural Network Channel Estimation for OFDM System
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作者：Kanchan Sharma ; Shweta Varshney
期刊名称：International Journal of Electronics and Computer Science Engineering
电子版ISSN：2277-1956
出版年度：2012
卷号：1
期号：3
页码：1686-1691
出版社：Buldanshahr : IJECSE
摘要：This paper uses Artificial Neural Network (ANN) for channel estimation based on Levenberg-Marquardt training algorithm in OFDM systems over Rayleigh fading channels. This technique utilizes the learning property of neural network. By using this feature, there is no need of any matrix computation and proposed technique is less complex. This technique is useful to achieving the high data rate, transmission capability with high bandwidth, efficiency and its robustness to multipath delay. In OFDM system, the Channel estimation is an essential problem so the Pilot-aided channel estimation has been used; a good choice of the pilot pattern should match the channel behavior both in time and frequency domains. In this arrangement, the performance of the channel estimation is analyzed with estimators based on Least Square Algorithm is carried out through MATLAB Simulation. The performance of OFDM with ANN is evaluated on the basis of Bit Error Rate (BER). The OFDM with ANN has been shown to perform much better than the OFDM without ANN
关键词：OFDM. Channel Estimation. Artificial Neural Netw ork. Least-Square Error