Channel Estimation Based on Neural Network in OFDM System for Powerline Communication

被引：0

作者：

Taspinar, Necmi ^{[1
]}

Sulev, Anil ^{[2
]}

机构：

[1] Erciyes Univ, Dept Elect & Elect Engn, Kayseri, Turkey

[2] Kayseri Ve Civari Elektrik TAS, Kayseri, Turkey

来源：

2013 INTERNATIONAL CONFERENCE ON ELECTRONICS, COMPUTERS AND ARTIFICIAL INTELLIGENCE (ECAI) | 2013年

关键词：

channel estimation; neural networks; OFDM; powerline channel;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, channel estimation based on neural network in powerline communication is proposed and its performance is compared with LS and MMSE methods by computer simulations using mean square error (MSE) and bit error rate (BER) criterias. The MSE and BER performances of neural network to estimate channel are between the LS and MMSE algorithms. MMSE algorithm yields the best performance but its complexity is high. The advantage of the use of the neural network is that the neural network yields better performance than the LS algorithm and it is less complex than the MMSE algorithm(1).

引用

页数：4

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