Performance Analysis of SWIPT Relay Networks over Arbitrary Dependent Fading Channels

TL;DR

This paper analyzes how the correlation between fading channels affects the performance of SWIPT relay networks, deriving formulas for capacity and outage probability under dependent Nakagami-m fading, validated by simulations.

Contribution

It introduces a general framework using copula theory to model correlated fading channels and derives closed-form expressions for key performance metrics in SWIPT relay networks.

Findings

Positive dependence improves system performance.

Negative dependence degrades system performance.

Performance improves with less severe fading.

Abstract

In this paper, we investigate the impact of fading channel correlation on the performance of dual-hop decode-and-forward (DF) simultaneous wireless information and power transfer (SWIPT) relay networks. More specifically, by considering the power splitting-based relaying (PSR) protocol for the energy harvesting (EH) process, we quantify the effect of positive and negative dependency between the source-to-relay (SR) and relay-to-destination (RD) links on key performance metrics such as ergodic capacity and outage probability. To this end, we first represent general formulations for the cumulative distribution function (CDF) of the product of two arbitrary random variables, exploiting copula theory. This is used to derive the closed-form expressions of the ergodic capacity and outage probability in a SWIPT relay network under correlated Nakagami-m fading channels. Monte-Carlo (MC) simulation results are provided throughout to validate the correctness of the developed analytical results, showing that the system performance significantly improves under positive dependence in the SR-RD links, compared to the case of negative dependence and independent links. Results further demonstrate that the efficiency of the ergodic capacity and outage probability ameliorates as the fading severity reduces for the PSR protocol.