Iterative joint source channel decoding in wireless sensor networks

Abstract

A novel soft-input-soft-output (SISO) a posteriori probability (APP) decoding algorithm for variable-length code (VLC) sequence is presented. This algorithm leads to maximum likelihood (ML) sequence estimation as well as the computation of bit-based reliability values that can be utilized in iterative joint source channel decoding (ISCD). At the same time, the algorithm requires low computational complexity and small memory space. This feature allows this technique to be applied in the wireless sensor networks (WSNs). Moreover, we bring the technique of scaling extrinsic information into the field of ISCD, and obtained the optimal fixed scaling factors (SFs) to refine the extrinsic information in our ISCD scheme. This technique clearly improves the ISCD performance with increasing neglectable complexity. Simulation results show that the proposed ISCD scheme provides a significant improvement on error protection capability for the variable-length coded data.