Abstract
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.
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