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Channel estimation by using ANN in DF based cooperative communication system

机译:基于DF的协作通信系统中基于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)受人脑信息处理技术的启发,最近在许多工程应用中发现了它的位置。特别是ANN的分类,建模和预测应用吸引了相当多的关注,因为ANN具有很高的性能。无线协作通信,一种通信系统,用户通过中继目的地进行通信。本文研究了基于人工神经网络的协作通信技术的误码性能。这种采用训练序列的技术是一种显着的方法,它通过消除对信道估计的需求来降低系统的复杂性和成本。 BPSK调制下的瑞利快速衰落信道的数值结果表明,所提出的方法可提供全分集增益。

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