This article is part of the series Turbo Processing.

Open Access Research Article

Iterative Code-Aided ML Phase Estimation and Phase Ambiguity Resolution

Henk Wymeersch* and Marc Moeneclaey

Author Affiliations

Digital Communications Research Group, Department of Telecommunications and Information Processing, Ghent University, Sint-Pietersnieuwstraat 41, Ghent 9000, Belgium

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EURASIP Journal on Advances in Signal Processing 2005, 2005:895349  doi:10.1155/ASP.2005.981


The electronic version of this article is the complete one and can be found online at: http://asp.eurasipjournals.com/content/2005/6/895349


Received: 29 September 2003
Revisions received: 25 May 2004
Published: 15 May 2005

© 2005 Wymeersch and Moeneclaey

As many coded systems operate at very low signal-to-noise ratios, synchronization becomes a very difficult task. In many cases, conventional algorithms will either require long training sequences or result in large BER degradations. By exploiting code properties, these problems can be avoided. In this contribution, we present several iterative maximum-likelihood (ML) algorithms for joint carrier phase estimation and ambiguity resolution. These algorithms operate on coded signals by accepting soft information from the MAP decoder. Issues of convergence and initialization are addressed in detail. Simulation results are presented for turbo codes, and are compared to performance results of conventional algorithms. Performance comparisons are carried out in terms of BER performance and mean square estimation error (MSEE). We show that the proposed algorithm reduces the MSEE and, more importantly, the BER degradation. Additionally, phase ambiguity resolution can be performed without resorting to a pilot sequence, thus improving the spectral efficiency.

Keywords:
turbo synchronization; phase estimation; phase ambiguity resolution; EM algorithm

Research Article