Improved decoding for binary source coding with coded side information

Anne Savard (1) , Claudio Weidmann (1)

1 ICI

This paper presents a new iterative decoding algorithm for the source coding with coded side information problem. Side information (SI) is compressed to an index by a many-to-one (quantization) function. Instead of using the reconstruction corresponding to the quantization index as a single representative SI word to aid the main decoder, one can modify it by projecting an intermediate estimate of the source word onto the Voronoi cell associated to the SI index. The hope is that the projection brings the representative SI word closer to the source word, and thus accelerates iterative decoding. Simulations using LDPC syndrome coding in the main branch and trellis-coded quantization in the SI branch show that for a fixed number of decoder iterations, this method indeed increases the number of correctly decoded source words. In fact, the decoding threshold is shifted, which may be attributed to a partial compensation of the suboptimality of the quantizer.

Domaines: Théorie de l'information [cs.IT]; Théorie de l'information et codage [math.IT]; Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

Anne Savard, Claudio Weidmann. Improved decoding for binary source coding with coded side information. 2013 IEEE Information Theory Workshop (ITW), Sep 2013, Sevilla, Spain. pp.1-5. ⟨hal-00863895⟩