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Open Access Research Article

A Systematic Approach to Modified BCJR MAP Algorithms for Convolutional Codes

Sichun Wang1* and François Patenaude2

Author Affiliations

1 Defence Research and Development Canada *#8211; Ottawa, Ottawa, ON, Canada, K1A 0Z4

2 Communications Research Centre Canada, Ottawa, ON, Canada, K2H 8S2

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EURASIP Journal on Advances in Signal Processing 2006, 2006:095360  doi:10.1155/ASP/2006/95360

The electronic version of this article is the complete one and can be found online at: http://asp.eurasipjournals.com/content/2006/1/095360

Received:19 November 2004
Revisions received:19 July 2005
Accepted:12 September 2005
Published:13 April 2006

© 2006 Wang and Patenaude

This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Since Berrou, Glavieux and Thitimajshima published their landmark paper in 1993, different modified BCJR MAP algorithms have appeared in the literature. The existence of a relatively large number of similar but different modified BCJR MAP algorithms, derived using the Markov chain properties of convolutional codes, naturally leads to the following questions. What is the relationship among the different modified BCJR MAP algorithms? What are their relative performance, computational complexities, and memory requirements? In this paper, we answer these questions. We derive systematically four major modified BCJR MAP algorithms from the BCJR MAP algorithm using simple mathematical transformations. The connections between the original and the four modified BCJR MAP algorithms are established. A detailed analysis of the different modified BCJR MAP algorithms shows that they have identical computational complexities and memory requirements. Computer simulations demonstrate that the four modified BCJR MAP algorithms all have identical performance to the BCJR MAP algorithm.


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