Mismatched Models to Lower Bound the Capacity of Dual-Polarization Optical Fiber Channels

Abstract

Regular perturbation is applied to the Manakov equation and motivates a generalized correlated phase-andadditive noise model for wavelength-division multiplexing over dual-polarization optical fiber channels. The model includes three hidden Gauss-Markov processes: phase noise, polarization rotation, and additive noise. Particle filtering is used to compute lower bounds on the capacity of multi-carrier communication with frequency-dependent powers and delays. A gain of 0.17 bits/s/Hz/pol in spectral efficiency or 0.8 dB in power efficiency is achieved with respect to existing models at their peak data rate. Frequency-dependent delays also increase the spectral efficiency of single-polarization channels.

Tailored Shaping, Improved Detection, Simpler Backpropagation: the Road to Nonlinearity Mitigation

“…The additional gain provided by SS is smaller in this case, since the optimization accounts only for intrachannel NLI and does not include PPN and DBP. Finally, including the per-subcarrier power optimization proposed in [27], [28] further improves the gain up to 1.36 bits/sym/pol.…”

“…Such components depend also on frequency and can be alternatively represented as time-varying linear ISI [23] . Their mitigation is possible [22], [24] and yields an increase of the AIR, which is more effective if combined with subcarrier multiplexing [25], [26] and an optimized per-subcarrier power allocation [27], [28] . Moreover, even the additive component of NLI has some correlation in time, which might be exploited for its mitigation [27], [28] .…”

Regular Perturbation and Achievable Rates of Space-Division Multiplexed Optical Channels

“…[s] 0 is a z-dependent phase shift, and the effect of β is a z-dependent delay. Similar to [20], the 2S entries of the S noise signals u ASE (z, t) are independent circularly-symmetric complex Gaussian (CSCG) processes. At the end of the fiber (z = L), their ACF for γ = 0 is…”

“…complex Gaussian with variance N ASE . Also as in [20], we neglect signal-noise mixing, and the nonlinear interference (NLI) becomes…”

“…We follow [19], [20] and develop an analysis for SDM by using the coupling equations in [21], [22], RP, and an approximation related to LP. The result is a correlated rotationand-additive noise (CRAN) model with correlated phase noise, spatial mode rotations, and additive noise.…”