Computationally Efficient Monitoring of PON Fiber Link Quality Using Periodic Coding

Abstract

We investigate experimentally and via simulation, the monitoring of fiber link quality in a PON using optical coding technology. We discuss design issues for periodic coding and the optimal detection criteria. We develop a reduced-complexity maximum-likelihood sequence estimation (RC-MLSE) algorithm. We conduct experiments to validate our detection algorithm using four periodic encoders that we designed and fabricated. Error-free detection is confirmed for encoders with separation as small as 1 m. Using the experimental data for the encoder impulse responses, we conduct Monte Carlo simulations for realistic PON geographical distributions with randomly located customers, again with error-free detection. We investigate the effect of coverage area and network size (number of subscribers) on the computational efficiency of our algorithm. We provide a bound on the probability that any given network will cause the algorithm to take exorbitant time to monitor the network, i.e., the time-out probability. Finally, we highlight the importance of averaging to remedy the power/loss budget limitations in our monitoring system to support higher network sizes and longer fiber reaches.