利用矩源函数确定l支路接收端K -µ衰落和SC联合CCI影响下的ABEP

D. Krstić, S. Suljovic, N. Petrovic, Sinisa Minic, Z. Popovic
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引用次数: 0

摘要

在这项工作中,将观察到由k-µ分布描述的小尺度衰落消失的有用信号,以及k-µ同信道干扰。研究了基于矩源函数(MGF)的l支路选择组合(SC)接收机在这些干扰影响下的平均误码率(ABEP)计算。为了分析衰落和同信道干扰参数的影响,将用图形显示结果。然后,提出了一种基于分类的机器学习方法,利用先前导出的ABEP值作为输入之一来估计服务质量(QoS)。为了实现,我们依靠PyTorch框架来实现神经网络,并与ZenML协同实现机器学习管道自动化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Determining the ABEP under the Influence of K -µ Fading and CCI with SC combining at L-branch Receiver Using Moment Generating Function
In this work, the useful signal suffering disappearance of small scale fading described by k-µ distribution, as well as k-µ co-channel disturbance, will be observed. The moment generating function (MGF)-based calculation of average bit error probability (ABEP) of L-branch selection combining (SC) receiver under the influence of these disturbances will be made. The results will be shown graphically in order to analyze influence of the fading and co-channel interference parameters. Then, a classification-based machine learning approach in order to estimate Quality of Service (QoS) making use of the previously derived ABEP value as one of the inputs is proposed. For implementation, we rely on PyTorch framework for neural networks in synergy with ZenML for machine learning pipeline automation.
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