Importance sampling techniques for estimating the bit error rate in digital communication systems

We are interested in estimating the bit error rate (BER) for signal transmission in digital communication systems. Since BERs tend to be extremely small, it is difficult to obtain precise estimators based on the use of crude Monte Carlo simulation techniques. In this paper, we review, expand upon, and evaluate a number of importance sampling variance reduction techniques for estimating the BER. We find that mixtures of certain "tailed" distributions with a uniform distribution produce estimators that are at least competitive with those in the literature. Our comparisons are based on analytical calculations and lay the groundwork for the evaluation of more general mixture distributions