2002Unpublished venueRequires access

Calculations of outage probabilities due to PMD using importance sampling

William L. Kath, Gino Biondini, I.P. Lima, B.S. Marks, Curtis R. Menyuk

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Abstract

We have shown how importance-sampled Monte-Carlo simulations provide an efficient method for computing the tails of the differential group delay (DGD) probability distribution due to polarization-mode dispersion (PMD). We have also applied this technique to study PMD compensators with an arbitrarily rotatable polarization controller and a single, fixed DGD element, demonstrating that for realistic power penalties the optimal DGD value used in the compensator can be two to three times larger than the mean DGD.

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What this paper is about

We have shown how importance-sampled Monte-Carlo simulations provide an efficient method for computing the tails of the differential group delay (DGD) probability distribution due to polarization-mode dispersion (PMD). We have also applied this technique to study PMD compensators with an arbitrarily rotatable polarization controller and a single, fixed DGD element, demonstrating that for realistic power penalties the optimal DGD value used in the compensator can be two to three times larger than the mean DGD.

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Available abstract

We have shown how importance-sampled Monte-Carlo simulations provide an efficient method for computing the tails of the differential group delay (DGD) probability distribution due to polarization-mode dispersion (PMD). We have also applied this technique to study PMD compensators with an arbitrarily rotatable polarization controller and a single, fixed DGD element, demonstrating that for realistic power penalties the optimal DGD value used in the compensator can be two to three times larger than the mean DGD.

Key concepts: Differential group delay, Polarization mode dispersion, Polarization controller, Monte Carlo method, Computer science, Importance sampling, Dispersion (optics), Polarization (electrochemistry)

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