MGF Based Calculation and Simulation of ABEP for Multi-branch SC Receiver in an Environment under α-K-μ Fading and Co-channel Interference

D. Krstić, S. Suljovic, N. Petrovic, Z. Popovic, Sinisa Minic
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引用次数: 4

Abstract

In this paper, a moment generating function (MGF)-based calculation of average bit error probability (ABEP) of multi-branch selection combining (SC) receiver under the influence of α-k-μ fading and α-k-μ co-channel interference will be carried out. The SC receiver is implemented to reduce the effects of multiple fading and interference on the bit error probability. The influence of parameters to the proposed radio communication system will be analyzed based on plotted graphs. Further, we introduce an approach aiming Quality of Service (QoS) estimation relying on classification using Weka machine learning Application Programming Interface (API) for Java, leveraging the calculated ABEP value as input variable. Several different classification algorithms were compared regarding accuracy and execution time. Decision table-based implementation gave the highest accuracy, while J48 decision tree shows just slightly lower rate, but has much faster training rate.
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α-K-μ衰落和同信道干扰下基于MGF的多支路SC接收机ABEP计算与仿真
本文研究了在α-k-μ衰落和α-k-μ同信道干扰影响下,基于矩源函数(MGF)的多支路选择组合(SC)接收机平均误码率(ABEP)的计算。为了降低多重衰落和干扰对误码概率的影响,设计了SC接收机。通过绘制图形分析了各参数对所提出的无线电通信系统的影响。此外,我们引入了一种基于分类的服务质量(QoS)估计方法,该方法使用Java的Weka机器学习应用程序编程接口(API),利用计算出的ABEP值作为输入变量。比较了几种不同的分类算法的准确率和执行时间。基于决策表的实现给出了最高的准确率,而J48决策树的准确率略低,但训练速度要快得多。
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