ABEP of a NFV-based 5G network with L-branch SC diversity under combined effects of η-µ fading and η-µ CCI

Abstract

In this paper we analyze the average bit error probability (ABEP) of a Network Function Virtualization (NFV)-based 5G system with an L-branch selection-combining (SC) receiver, in a composite η-µ fading and η-µ co-channel interference (CCI) environment. We derive closed-form expressions for cumulative distribution function (CDF) and moment generating function (MGF) and find the ABEP for the non-coherent binary frequency shift keying (BFSK) and binary differential phase shift keying (BDPSK) modulation. We present the numerical and simulation results for a different number of diversity branches and different values of parameters η and µ. Additionally, we introduce an approach to Quality of Service (QoS) estimation by leveraging supervised machine learning classification techniques in Java programming language relying on Weka API. The obtained ABEP value is considered as one of the input variables and QoS is compared for four different classification algorithms.