Compression with side information using turbo codes

TLDR

In the asymmetric scenario considered, X and Y are statistically dependent signals and X is encoded with no knowledge of Y, but Y is known as side information at the decoder. The study demonstrates that turbo codes can approach the Slepian‑Wolf bound in lossless distributed source coding. We use a turbo‑code‑based system to encode X at a rate close to H(X|Y) with Y available as side information at the decoder. Simulations on binary sequences show performance near the information‑theoretic limit, Gaussian sequence coding yields significant improvement over prior work, and the scheme also performs well for joint source‑channel coding.

Abstract

We show that turbo codes can come close to the Slepian-Wolf bound in lossless distributed source coding. In the asymmetric scenario considered, X and Y are statistically dependent signals and X is encoded with no knowledge of Y. However, Y is known as side information at the decoder. We use a system based on turbo codes to send X at a rate close to H(X|Y). We apply our system to binary sequences and simulations show performance close to the information-theoretic limit. For distributed source coding of Gaussian sequences, our results show significant improvement over previous work. The scheme also performs well for joint source-channel coding.