Multicanonical Monte Carlo for Simulation of Optical Links

Part of the Optical and Fiber Communications Reports book series (OFCR, volume 7)


Multicanonical Monte Carlo (MMC) is a simulation-acceleration technique for the estimation of the statistical distribution of a desired system output variable, given the known distribution of the system input variables. MMC, similarly to the powerful and well-studied method of importance sampling (IS) [1], is a useful method to efficiently simulate events occurring with probabilities smaller than ∼ 10 − 6, such as bit error rate (BER) and system outage probability. Modern telecommunications systems often employ forward error correcting (FEC) codes that allow pre-decoded channel error rates higher than 10 − 3; these systems are well served by traditional Monte-Carlo error counting. MMC and IS are, nonetheless, fundamental tools to both understand the statistics of the decision variable (as well as of any physical parameter of interest) and to validate any analytical or semianalytical BER calculation model. Several examples of such use will be provided in this chapter. As a case in point, outage probabilities are routinely below 10 − 6, a sweet spot where MMC and IS provide the most efficient (sometimes the only) solution to estimate outages.


Probability Density Function Markov Chain Monte Carlo Monte Carlo Forward Error Correction Semiconductor Optical Amplifier 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



It is a pleasure to acknowledge A. Ghazisaeidi and F. Vacondio of Laval University, and N. Rossi, A. Orlandini, P. Serena and A. Vannucci of Parma University, for the many stimulating discussions and for their producing the numerical examples in the text.


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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.Dipartimento di Ingegneria dell’InformazioneUniversità di ParmaParmaItaly
  2. 2.Electrical and Computer Engineering DepartmentUniversité LavalQuébec CityCanada

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