Generalized Physical Layer Channel Model for Relay-Based Super Dense Networks

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The κ-μ fading model is an advanced channel model in super dense wireless networks.In this paper,we evaluate the performance of the system over κ-μ fading channel in super dense relay networks with consideration of multiple independent but not necessarily identically distributed(i.n.i.d.) cochannel interference(CCI) under interferencelimited environment.More specifically,we derive a useful and accurate cumulative distribution function(CDF) expression of the end-to-end signal-to-interference plus noise(SINR) ratio.Moreover,we derive novel analytical expressions of the outage probability(OP),average bit error probability(ABEP) and average capacity for binary modulation types and arbitrary positive values of κ-and μ of such system.Furthermore,we propose asymptotic analysis for both the OP and ABEP to give physical insights.A simplified analytical form for the ABEP at high-SNR regimes is provided as well.Finally,the accuracy of the derived expressions is well validated by Monte Carlo simulations. The κ-μ fading model is an advanced channel model in super dense wireless networks. In this paper, we evaluate the performance of the system over κ-μ fading channel in super dense relay networks with consideration of multiple independent but not necessarily identically distributed inid) cochannel interference (CCI) under interferencelimited environment. Specifically, we derive a useful and accurate cumulative distribution function (CDF) expression of the end-to-end signal-to- interference plus noise novel analytical expressions of the outage probability (OP), average bit error probability (ABEP) and average capacity for binary modulation types and arbitrary positive values ​​of κ-and μ of such systems. Further eds, we propose asymptotic analysis for both the OP and ABEP to give physical insights. A simplified analytical form for the ABEP at high-SNR regimes is provided as well. Finaally, the accuracy of the derived expressions is well validated by Monte Carlo simulations.
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