Iterative Detection and Phase-Noise Compensation for Coded Multichannel Optical Transmission

The problem of phase-noise compensation for correlated phase noise in coded multichannel optical transmission is investigated. To that end, a simple multichannel phase-noise model is considered and the maximum a posteriori detector for this model is approximated using two frameworks, namely factor graphs (FGs) combined with the sum–product algorithm (SPA), and a variational Bayesian (VB) inference method. The resulting pilot-aided algorithms perform iterative phase-noise compensation in cooperation with a decoder, using extended Kalman smoothing to estimate the a posteriori phase-noise distribution jointly for all channels. The system model and the proposed algorithms are verified using experimental data obtained from space-division multiplexed multicore-fiber transmission. Through Monte Carlo simulations, the algorithms are further evaluated in terms of phase-noise tolerance for coded transmission. It is observed that they significantly outperform the conventional approach to phase-noise compensation in the optical literature. Moreover, the FG/SPA framework performs similarly or better than the VB framework in terms of phase-noise tolerance of the resulting algorithms, for a slightly higher computational complexity

Extended Kalman Filter for MIMO Phase Noise Channels with Independent Oscillators

The Kalman filter is proposed here to track the phase noise introduced by independent transmit and receive oscillators in multiple-input multiple-output transmission. To take advantage of pilot symbols that are transmitted before and after the time instant where one wants to estimate the vector of phases, a forward-backward Kalman filter is proposed. To reduce the complexity of the Kalman filter, suboptimal methods are introduced and their performance is compared to that of the full complexity Kalman filter by computer simulation