Interplay of Probabilistic Shaping and the Blind Phase Search Algorithm

TL;DR

This paper investigates how probabilistic shaping affects the performance of the blind phase search algorithm in optical communication systems, revealing that shaping influences phase recovery and can cause implementation penalties.

Contribution

It provides a detailed analysis of the interaction between probabilistic shaping and the blind phase search algorithm, including theoretical bounds and simulation results.

Findings

Probabilistic shaping impacts the supervised phase search performance.

Blind phase search is affected by probabilistic shaping even with long windows.

Capacity-maximizing shaping can lead to worst-case scenarios for BPS.

Abstract

Probabilistic shaping (PS) is a promising technique to approach the Shannon limit using typical constellation geometries. However, the impact of PS on the chain of signal processing algorithms of a coherent receiver still needs further investigation. In this work we study the interplay of PS and phase recovery using the blind phase search (BPS) algorithm, which is widely used in optical communications systems. We first investigate a supervised phase search (SPS) algorithm as a theoretical upper bound on the BPS performance, assuming perfect decisions. It is shown that PS influences the SPS algorithm, but its impact can be alleviated by moderate noise rejection window sizes. On the other hand, BPS is affected by PS even for long windows because of correlated erroneous decisions in the phase recovery scheme. The simulation results also show that the capacity-maximizing shaping is near to the BPS worst-case situation for square-QAM constellations, causing potential implementation penalties.