Neural network implementation of the BCJR algorithm

Authors:
Murat Hüsnü Sazlı;Can Işık
Affiliations:
Faculty of Engineering, Electronics Engineering Department, Ankara University, Tandogan 06100, Ankara, Turkey;L.C. Smith College of Engineering and Computer Science, Department of Electrical Engineering and Computer Science, Syracuse University, Syracuse, NY 13244, USA
Venue:
Digital Signal Processing
Year:
2007

Citing 2
Cited 0

Applications of neural networks to digital communications: a survey

Signal Processing - Special issue on emerging techniques for communication terminals
Optimal decoding of linear codes for minimizing symbol error rate (Corresp.)

IEEE Transactions on Information Theory

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, we first show that the BCJR algorithm (or Bahl algorithm) can be implemented via some matrix manipulations. As a direct result of this, we also show that this algorithm is equivalent to a feedforward neural network structure. We verified through computer simulations that this novel neural network implementation yields identical results with the BCJR algorithm.