binary wyner-ziv and ceo problem coding under the hamming distortion criterion

In this paper, we present a practical encoding and decoding scheme for the binary wyner-ziv problem based on graph-based codes. our proposed scheme uses low-density generator-matrix (ldgm) codes in lossy source coding part and low-density parity-check (ldpc) codes in syndrome generation and decoding part. actually, we apply bias-propagation algorithm for lossy source coding or binary quantization and sum-product algorithm for syndrome-based channel decoding. using appropriate degree distributions for ldgm codes and optimized degree distributions for ldpc codes, we will be able to achieve close rate-distortion performance to the theoretical wyner-ziv bound. also, we extend our proposed scheme for presenting a practical coding scheme for the binary chief executive officer (ceo) problem. in our scheme, encodig is based on binary-quantization and slepian-wolf coding using source-splitting technique. it is shown that, source-splitting technique is an efficient strategy for achieving non-corner points in slepian-wolf rate region. we show that, this technique along with iterative message-passing algorithms can be efficient for having close rate-distortion performance to the berger-tung inner bound of binary ceo problem for non-corner points too.