Data compression of correlated non-binary sources using punctured turbo codes

We consider the case of two correlated non-binary sources. Data compression is achieved by transforming the sequences of non-binary symbols into sequences of bits and then using punctured turbo codes as source encoders. Each source is compressed without knowledge about the other source, and no information about the correlation between sources is required in the encoding process. Compression is achieved because of puncturing, which is adjusted to obtain the desired compression rate. The source decoder utilizes iterative schemes over the compressed binary sequences, and recovers the non-binary symbol sequences from both sources. The performance of the proposed scheme is close to the theoretical limit predicted by the Slepian-Wolf (1973) theorem.