BCJR algorithm

Error correction algorithm

The Bahl-Cocke-Jelinek-Raviv (BCJR) algorithm is an algorithm for maximum a posteriori decoding of error correcting codes defined on trellises (principally convolutional codes). The algorithm is named after its inventors: Bahl, Cocke, Jelinek and Raviv.^[1] This algorithm is critical to modern iteratively-decoded error-correcting codes, including turbo codes and low-density parity-check codes.

Steps involved

Based on the trellis:

Compute forward probabilities $\alpha$ {\displaystyle \alpha }
Compute backward probabilities $\beta$ {\displaystyle \beta }
Compute smoothed probabilities based on other information (i.e. noise variance for AWGN, bit crossover probability for binary symmetric channel)

Berrou, Glavieux and Thitimajshima simplification.^[2]

This section needs expansion. You can help by adding to it. (September 2022)

Susa framework implements BCJR algorithm for forward error correction codes and channel equalization in C++.

^ Bahl, L.; Cocke, J.; Jelinek, F.; Raviv, J. (March 1974). "Optimal Decoding of Linear Codes for minimizing symbol error rate". IEEE Transactions on Information Theory. 20 (2): 284–7. doi:10.1109/TIT.1974.1055186.
^ Wang, Sichun; Patenaude, François (2006). "A Systematic Approach to Modified BCJR MAP Algorithms for Convolutional Codes". EURASIP Journal on Applied Signal Processing. 2006: 95360. Bibcode:2006EJASP2006..242W. doi:10.1155/ASP/2006/95360 .
^ Robertson, P.; Hoeher, P.; Villebrun, E. (1997). "Optimal and Sub-Optimal Maximum A Posteriori Algorithms Suitable for Turbo Decoding". European Transactions on Telecommunications. 8 (2): 119–125. doi:10.1002/ett.4460080202 .