Bayesian Phase Search for Probabilistic Amplitude Shaping

TL;DR

This paper presents a Bayesian carrier phase recovery algorithm designed to improve phase estimation in probabilistic amplitude shaping systems, especially under low signal-to-noise ratio conditions.

Contribution

The paper introduces a novel Bayesian CPR algorithm that enhances phase recovery robustness for PAS, outperforming traditional blind phase-search methods.

Findings

The Bayesian CPR algorithm is effective in low SNR scenarios.

It overcomes limitations of blind phase-search CPR for PAS.

Experimental results validate improved phase recovery accuracy.

Abstract

We introduce a Bayesian carrier phase recovery (CPR) algorithm which is robust against low signal-to-noise ratio scenarios. It is therefore effective for phase recovery for probabilistic amplitude shaping (PAS). Results validate that the new algorithm overcomes the degradation experienced by blind phase-search CPR for PAS.