Complexity of Distributed Source Coding using LDPCA Codes
Min Jang, Jin-Whan Kang, Sang‐Hyo Kim · 2010
Distributed source coding (DSC) system moves computational burden from encoder to decoder, so it takes higher decoding complexity. This paper explores the problem of reducing the decoding complexity of practical Slepian-Wolf coding using low-density parity check accumulate (LDPCA) codes. It is shown that the convergence of mean magnitude (CMM) stopping criteria for LDPC codes help reduce the 85% of decoding complexity under the 2% of compression rate loss, and marginal initial rate request reduces complexity below complexity minimum bound. Moreover, inter-rate stopping criterion, modified for rate-adaptable characteristic, is proposed for LDPCA codes, and it makes decoder perform less iterative decoding than normal stopping criterion does when channel characteristic is unknown.