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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