Enhanced Regular Perturbation-Based Nonlinearity Compensation Technique for Optical Transmission Systems

Abstract

The regular perturbation (RP) series used to analytically approximate the solution of the nonlinear Schrodinger equation has a serious energy-divergence problem when truncated to the first order. The enhanced RP (ERP) method can improve the accuracy of the first-order RP approximation by solving the energy divergence problem. In this paper, we propose an ERP-based nonlinearity compensation technique, referred to as ERP-NLC, to compensate for the fiber nonlinearity in a polarization-division multiplexed dispersion unmanaged optical communication system. We also propose a modified perturbation-based NLC (PB-NLC) technique by simple phase-rotation (PR) of the nonlinear coefficient matrix, referred to as the PR-PB-NLC. The PR-PB-NLC can be considered as a by-product of the ERP-NLC technique. We show through numerical simulation that, for a 256 Gb/s singlechannel system, the proposed ERP-NLC technique improves the Q-factor performance by ∼1.2 dB and ∼0.6 dB when compared to the electronic dispersion compensation (EDC) and the PB-NLC techniques, respectively, at a transmission distance of 2800 km. Also, the result for a 1.28 Tb/s wavelength-division multiplexed five-channel transmission system at the same transmission distance shows that the Q-factor performance of the ERP-NLC technique is improved by ∼0.6 dB and ∼0.4 dB when compared to the EDC and the PB-NLC techniques, respectively. The simulation results for the PR-PB-NLC technique for a single-or five-channel transmission system show an improved Q-factor performance when compared to the EDC and PB-NLC techniques. Finally, we show that the proposed performance enhancement comes with a negligible increase in the computational complexity for the ERP-NLC and PR-PB-NLC techniques when compared to the PB-NLC technique.

A tutorial on fiber Kerr nonlinearity effect and its compensation in optical communication systems

“…It is important to note that (114) is the same as the Manakov equation given in (74), in which ( 114) is written in a more compact form by omitting the space and time variables z, t for the sake of simplicity. By solving (114), the zeroth-and first-order solutions can be written as [40]:…”

“…In the PDM optical system, the input signal field to the fiber is a column vector u(z, t) = [u x (z, t) u y (z, t)] † , where x, y are the polarization tributaries, and † is the transpose. The vector field propagation in the optical fiber is governed by the Manakov equation, which is given as [40]: where I is the identity matrix. It is important to note that (114) is the same as the Manakov equation given in (74), in which ( 114) is written in a more compact form by omitting the space and time variables z, t for the sake of simplicity.…”

“…The first-order perturbation theory-based NLC (PB-NLC) technique adopts some simplifying assumptions, including [38,40,[46][47][48][49]:…”

“…Without loss of generality, the nonlinear distortion field induced at index k = 0, i.e. l = m + n is calculated at t = 0 by considering the symbol rate operation [38,40,[46][47][48][49]. Accordingly, (117) can be further simplified as [37,38,40,[46][47][48][49]: where * represents the complex conjugate operation and C m,n is the first-order perturbation coefficient matrix, which is given as [37,38,40,[46][47][48][49]:…”

Fiber Nonlinearity and Tight Filtering Impairments Mitigation of DP-16QAM Nyquist-WDM Systems Using Multiplier-Free MAP Detection

“…Various approaches have been proposed to compensate/mitigate above impairments using Tx-and/or Rx-side DSP. The current mainstream techniques for fiber nonlinear effect compensation include digital back-propagation (DBP) algorithms [13]- [16], time/frequency-domain Volterra series-based equalizers [17]- [19], machine learning-based techniques [20]- [22], nonlinear Fourier transform (NFT) [23], maximum likelihood sequence estimation (MLSE) [24], [25], and regular perturbation-based methods [26]. However, most of the methods mentioned above require detailed knowledge of the transmitted signals and generally groan under the intolerable burden of massive CC, thereby hindering their practical application.…”