A Fresh Look at Multicanonical Monte Carlo from a Telecom Perspective

The Multicanonical Monte Carlo (MMC) technique is a new form of adaptive importance sampling (IS). Thanks to its blind adaptation algorithm, it does not require an in-depth system knowledge for exploitation as does traditional IS. Hence MMC is a practical, handy tool to estimate via simulation the probability of rare events in complex telecom systems, such as the symbol error rate or the outage probability. In this paper, we present the analytical connections between MMC and IS, and describe the recursive algorithm via which MMC seeks an optimal "flat-histogram" warping. We also provide practical guidelines on how MMC can be successfully applied in telecom to achieve accelerations of simulation time by many orders of magnitude with respect to standard Monte Carlo.