Channel-optimized soft trellis waveform coding

We provide a new fuzzy relaxation trellis code-book search algorithm over noisy channels. The new algorithm solves the problems associated with the LBG algorithm, in the sense of delivering relatively lower distortion configurations using short training sequences. Furthermore, the new approach is significantly less sensitive to the initialization process. The algorithm minimizes a weighted distortion measure averaged over both the source and the channel statistics. The weights are soft distortion-related reliability information, which are delivered by a soft trellis vector quantization algorithm (STVQ). The concept of soft compression is introduced by Haddad and Yongacoglu (see Proceedings of GLOBECOM'99, Rio de Janeiro, Brazil, 1999) using the forward-backward symbol-MAP algorithm. The work introduced in this paper is an extension to the work established for the noiseless channel case discussed by Haddad and Yongacoglu (see IEEE ICASSP 2000, Istanbul, Turkey, p.1882-6, 2000). Testing is performed using a first order Gauss-Markov source over several trellis structures.