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Channel estimation by using ANN in DF based cooperative communication system

机译:基于DF的合作通信系统中的ANN的信道估计

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Artificial neural networks (ANN) have been inspired by the human brain information processing techniques has recently found its place in many engineering applications. In particular, classification, modeling and prediction applications of ANN have attracted quite attention because ANN provides high performance. The wireless cooperative communication, a communication system in which users are communicating through a relay destination. In this paper, error performance of ANN based cooperative communication technique is studied. This technique, which employs training sequences, is a prominent approach for decreasing the system complexity and cost by eliminating the need for channel estimation. The numerical results for Rayleigh fast fading channels over BPSK modulation have shown that proposed approach provides full diversity gain.
机译:人工神经网络(ANN)受到了人类脑信息处理技术最近发现其在许多工程应用中的位置。特别是,ANN的分类,建模和预测应用引起了非常关注的,因为ANN提供高性能。无线协作通信,用户通过中继目的地通信的通信系统。本文研究了基于ANN基于合作通信技术的误差性能。这种采用训练序列的技术是通过消除对信道估计的需求来降低系统复杂性和成本的突出方法。在BPSK调制上,Rayleigh快速衰落通道的数值结果表明,所提出的方法提供全部多样化增益。

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