  We propose a unified rare-event estimator for the performance evaluation of
wireless communication systems. The estimator is derived from the well-known
multilevel splitting algorithm. In its original form, the splitting algorithm
cannot be applied to the simulation and estimation of time-independent
problems, because splitting requires an underlying continuous-time Markov
process whose trajectories can be split. We tackle this problem by embedding
the static problem of interest within a continuous-time Markov process, so that
the target time-independent distribution becomes the distribution of the Markov
process at a given time instant. The main feature of the proposed multilevel
splitting algorithm is its large scope of applicability. For illustration, we
show how the same algorithm can be applied to the problem of estimating the
cumulative distribution function (CDF) of sums of random variables (RVs), the
CDF of partial sums of ordered RVs, the CDF of ratios of RVs, and the CDF of
weighted sums of Poisson RVs. We investigate the computational efficiency of
the proposed estimator via a number of simulation studies and find that it
compares favorably with existing estimators.
