AG Kommunikationstheorie


Combination of LDPC codes and compressed sensing: a basic idea to design CS matrices


Low density parity-check (LDPC) codes, discovered by Gallager in 1962, are currently the most promising coding technique for error control in communication and data storage systems due to their capacity-approaching performances and practically implementable decoding algorithms. On the other hand, recent years have seen an explosion of research activities in a fascinating area called compressed sensing (CS), which can reconstruct signals from underdetermined measurements smaller than the signal length. Interestingly, the two research fields have something in common, i.e., both need some matrices, called sparse parity-check matrices in LDPC community, and measurement matrices in CS domain, respectively. In this talk, the requirements for the matrices in the two research areas are reviewed, and the possible ways to design measurement matrices is introduced by using some matrices for LDPC codes.

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