Calculating PMD statistics and outage probabilities with importance sampling

This paper describes the application of importance sampling to Monte-Carlo simulations of polarization-mode dispersion (PMD) in optical fibers. We have shown that importance sampling biases Monte-Carlo simulations of concatenated birefringent sections so that large first-and/or second-order PMD values occur more frequently than they would normally. The method also allows the effect of PMD on system outage probabilities to be assessed at realistic levels. PMD can be a major impairment in optical transmission systems. To first order in frequency, PMD splits a pulse between the fast and slow fiber axes; at the same time, higher-order PMD induces depolarization and polarization-dependent chromatic dispersion. We have shown that importance sampling biases Monte-Carlo simulations of concatenated birefringent sections so that large first-and/or second-order PMD values occur more frequently than they would normally. Importance-sampled Monte-Carlo techniques thus provide a natural and effective tool to assess PMD statistics and PMD-induced impairments in optical transmission systems at realistic probability levels.