Efficiency of optimal conditional importance sampling
Lei Wei · Electronics Letters · 1995
Optimal conditional importance sampling (OCIS) provides the unique optimal conditional estimator for error probabilities. The OCIS method essentially obtains a Monte Carlo average over conditional error probabilities. The efficiency of OCIS is studied for a binary symmetric ISI channel with AWGN. The results show that the technique is at least twice as efficient as that of the linearly shifted method.