DS-CDMA blind detection for frequency-selective multipath channels by neural networks

Majid Shakhsi Dastgahian, H. Khoshbin, S. Shaerbaf, A. Seyedin
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引用次数: 2

Abstract

Up to now, various detection algorithms have been offered and investigated for DS-CDMA systems in multipath conditions. Here, We intend to implement sub-optimum receivers based on Maximum-Ratio-Combining (MRC) via neural network structures in Downlink systems. We will demonstrate that our design based on Radial Base function (RBF) and Multi Layer Perceptron (MLP) outperform in comparison of conventional detectors such as Match-Filter, Decorrelator Detector (DD) and MMSE manner. We also propose a new method when receiver doesn't know sequence code in CDMA receiver system and illustrate that RBF is proper when number of users are low and MLP is prefer where the number of users increased.
基于神经网络的DS-CDMA选频多径信道盲检测
目前,针对多径条件下的DS-CDMA系统,已经提出并研究了各种检测算法。在这里,我们打算通过神经网络结构在下行链路系统中实现基于最大比率组合(MRC)的次优接收器。我们将证明我们基于径向基函数(RBF)和多层感知器(MLP)的设计优于传统的检测器,如匹配滤波器,去相关检测器(DD)和MMSE方式。在CDMA接收系统中,针对接收机不知道序列码的情况,提出了一种新的方法,并说明了在用户数量较少时,RBF是合适的,而在用户数量增加时,MLP是最好的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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