Iterative joint source channel decoding for WMSN

Abstract

An iterative joint source channel decoding (ISCD) scheme for WMSN is proposed, based on a soft-input-soft-output (SISO) a posteriori probability decoding algorithm for variable-length coded sources, which leads to not only maximum likelihood (ML) sequence estimation but also the computation of bit-based reliability values which are necessary for ISCD. Another innovation is that the technique of scaling extrinsic information is brought into the field of ISCD, and the optimal constant scaling factors is obtained under the guide of extrinsic information transfer characteris- tic. This technique improves the ISCD performance with increasing neglectable complexity. The notable feature of the proposed technique is that it requires very low computational complexity and small memory space, and can be applied to WMSN nodes. Simulation results show that the proposed ISCD scheme provides a significant improvement on error pro- tection capability for the variable-length coded data in WMSN.

Cite this paper

@article{yi2008iterative,
  title = {{Iterative joint source channel decoding for WMSN}},
  author = {Yi, Weidong},
  year = {2008}
}

Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.

Related papers