Phase estimation and phase ambiguity resolution by message passing

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Abstract

Several code-aided algorithms for phase estimation have recently been proposed. While some of them are ad-hoc, others are derived in a systematic way. The latter can be divided into two different classes: phase estimators derived from the expectation-maximization (EM) principle and estimators that are approximations of the sum-product message passing algorithm. In this paper, the main differences and similarities between these two classes of phase estimation algorithms are outlined and their performance and complexity is compared. Furthermore, an alternative criterion for phase ambiguity resolution is presented and compared to an EM based approach proposed earlier. © Springer-Verlag 2004.

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APA

Dauwels, J., Wymeersch, H., Loeliger, H. A., & Moeneclaey, M. (2004). Phase estimation and phase ambiguity resolution by message passing. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3124, 150–155. https://doi.org/10.1007/978-3-540-27824-5_22

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