Iterative Decoding and Phase-Noise Compensation for Multichannel Optical Transmission

The problem of phase-noise compensation for correlated phase noise in coded multichannel optical transmission is investigated. To that end, a multichannel phase-noise model is introduced and the maximum a posteriori detector for this model is approximated using two frameworks, namely factor graphs (FGs) and the sum–product algorithm (SPA), as well as a variational Bayesian (VB) inference. The resulting pilot-aided algorithms perform phase-noise compensation in cooperation with an iterative decoder, using extended Kalman smoothing to estimate the a posteriori phase-noise distribution jointly for all channels. Through Monte Carlo simulations, the algorithms are assessed in terms of phase-noise tolerance for coded transmission. It is observed that they significantly outperform the conventional approach of performing phase-noise compensation separately for each channel. Moreover, the results reveal that the FG/SPA framework performs similarly or better than the VB framework in terms of phase-noise tolerance of the resulting algorithms.