Domenico Marsella

Maximum Likelihood Sequence Detection for Mitigating Nonlinear Effects

Coherent detection allows for a more effective compensation of transmission impairments in the electrical domain. However, in order to be effective, a detection strategy should be based on an accurate channel model capable of providing sufficiently accurate signal statistics. While in the linear regime such a model is available and linear impairments such as chromatic dispersion and polarization-mode dispersion can be almost fully compensated by adaptive equalizers, this is not the case for nonlinear impairments, whose mitigation is essentially based on heuristic strategies. One of the most considered strategies is the back-propagation (BP) technique, based on channel inversion. It is shown that BP is most effective only in dispersion-unmanaged links, while a low-complexity Viterbi detector with proper metrics can achieve better results in the case of dispersion-managed links. It is also shown that, in the cases where it is effective, BP is far from approaching optimal performance. Indeed, proper processing after BP can significantly increase performance.

Enhanced Split-Step Fourier Method for Digital Backpropagation

An enhanced version of the popular split-step Fourier method (SSFM) is presented. When used for digital backpropagation, the enhanced method allows a complexity reduction of up to one order of magnitude with respect to standard SSFM without sacrificing performance.

Stochastic Digital Backpropagation With Residual Memory Compensation

Stochastic digital backpropagation (SDBP) is an extension of digital backpropagation (DBP) and is based on the maximum a posteriori principle. SDBP takes into account noise from the optical amplifiers in addition to handling deterministic linear and nonlinear impairments. The decisions in SDBP are taken on a symbol-by-symbol (SBS) basis, ignoring any residual memory, which may be present due to nonoptimal processing in SDBP. In this paper, we extend SDBP to account for memory between symbols. In particular, two different methods are proposed: a Viterbi algorithm (VA) and a decision directed approach. Symbol error rate (SER) for memory-based SDBP is significantly lower than the previously proposed SBS-SDBP. For inline dispersion-managed links, the VA-SDBP has up to 10 and 14 times lower SER than DBP for QPSK and 16-QAM, respectively.

On maximum likelihood sequence detectors for single-channel coherent optical communications

Two different detectors that account for the nonlinear signal-noise interaction in a single-channel coherent optical link are compared. The results indicate that accounting for the correlation between the samples leads to improved performance over stochastic digital backpropagation.

On the use of factor graphs in optical communications

Factor graphs and message passing allow the near-automated development of algorithms in many engineering disciplines, including digital communications. This paper gives an overview of their possible use in optical communications.

Receiver Training for Efficient Nonlinear Equalization and Detection in Optical Communications

The logarithmic-perturbation model is employed to design equalization and detection schemes for nonlinear fiber-optic systems, whose parameters are estimated and updated by proper training algorithms. Effective mitigation of intra- and inter-channel nonlinearity is demonstrated.

Detection strategies in the presence of fiber nonlinear effects

All known compensation techniques for combating fiber nonlinearities, including digital back-propagation (BP), are far from being optimal. However, it is shown that a low-complexity Viterbi detector with proper metrics is a good alternative or complement to BP for approaching optimal performance.