A Variational Bayes Approach to Decoding in a Phase-Uncertain Digital Receiver

TL;DR

This paper introduces a Bayesian variational approach for joint symbol and phase decoding in digital receivers, extending previous methods to multi-symbol scenarios with improved robustness in low SNR conditions.

Contribution

It extends the Bayesian framework to multi-symbol phase inference using variational Bayes, providing a more robust alternative to EM-based methods in phase-unsynchronized digital receivers.

Findings

Enhanced decoding robustness in low SNR regimes

Effective handling of phase ambiguity through prior regularization

Extension of Bayesian methods to multi-symbol phase inference

Abstract

This paper presents a Bayesian approach to symbol and phase inference in a phase-unsynchronized digital receiver. It primarily extends [Quinn 2011] to the multi-symbol case, using the variational Bayes (VB) approximation to deal with the combinatorial complexity of the phase inference in this case. The work provides a fully Bayesian extension of the EM-based framework underlying current turbo-synchronization methods, since it induces a von Mises prior on the time-invariant phase parmeter. As a result, we achieve tractable iterative algorithms with improved robustness in low SNR regimes, compared to the current EM-based approaches. As a corollary to our analysis we also discover the importance of prior regularization in elegantly tackling the significant problem of phase ambiguity.