Probabilistic Amplitude Shaping and Nonlinearity Tolerance: Analysis and Sequence Selection Method

TL;DR

This paper analyzes how probabilistic amplitude shaping (PAS) influences nonlinear interference in optical fibers, introduces a linear filter model for understanding this effect, and proposes a sequence selection method to improve nonlinearity tolerance.

Contribution

It introduces a linear lowpass filter model to analyze PAS's nonlinear effects and proposes a new sequence selection metric for enhanced nonlinearity mitigation.

Findings

The model explains existing literature results.

Sequence selection improves nonlinearity tolerance.

Simulations validate the effectiveness of the new metric.

Abstract

Probabilistic amplitude shaping (PAS) is a practical means to achieve a shaping gain in optical fiber communication. However, PAS and shaping in general also affect the signal-dependent generation of nonlinear interference. This provides an opportunity for nonlinearity mitigation through PAS, which is also referred to as a nonlinear shaping gain. In this paper, we introduce a linear lowpass filter model that relates transmitted symbol-energy sequences and nonlinear distortion experienced in an optical fiber channel. Based on this model, we conduct a nonlinearity analysis of PAS with respect to shaping blocklength and mapping strategy. Our model explains results and relationships found in literature and can be used as a design tool for PAS with improved nonlinearity tolerance. We use the model to introduce a new metric for PAS with sequence selection. We perform simulations of selection-based PAS with various amplitude shapers and mapping strategies to demonstrate the effectiveness of the new metric in different optical fiber system scenarios.