Compression of correlated sources using LDPC codes

Summary form only given. The problem of compressing correlated binary sources when the correlation between sources is defined by a hidden Markov model (HMM) was considered. Specifically, the HMM describes the correlation pattern such as the modulo-2 addition of the two sources. A density evolution analysis of a compression system was developed using irregular LDPC codes as source codes. To achieve this goal, the standard density evolution approach was modified to incorporate the HMM. It was then applied to the design of irregular codes to optimize system performance. The key to the incorporation of HMM in density evolution is to find the input-output characteristic of the forward-backward (F-B) decoding algorithm. The output of the F-B block subtitles the a priori message in the traditional density evolution case. Theoretical results agree with the simulations and show that it is possible to achieve a performance loss close to the theoretical Slepian-Wolf limit.