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In this work, we evaluate the outage probability (OP) for L-branch equal gaincombining (EGC) diversity receivers operating over fading channels, i.e.equivalently the cumulative distribution function (CDF) of the sum of the Lchannel envelopes. In general, closed form expressions of OP values areunobtainable. The use of Monte Carlo (MC) simulations is not considered a goodalternative as it requires a large number of samples for small values of OP,making MC simulations very expensive. In this paper, we use the concept ofimportance sampling (IS), being known to yield accurate estimates using fewersimulation runs. Our proposed IS scheme is essentially based on samplerejection where the IS probability density function (PDF) is the truncation ofthe underlying PDF over the L dimensional sphere. It assumes the knowledge ofthe CDF of the sum of the L channel gains in a closed-form expression. Such anassumption is not restrictive since it holds for various challenging fadingmodels. We apply our approach to the case of independent Rayleigh, correlatedRayleigh, and independent and identically distributed Rice fading models. Next,we extend our approach to the interesting scenario of generalised selectioncombining receivers combined with EGC under the independent Rayleigh fadingenvironment. For each case, we prove the desired bounded relative errorproperty. Finally, we validate these theoretical results through some selectedexperiments.

An Accurate Sample Rejection Estimator for the Estimation of Outage Probability of EGC Receivers