Energy efficient data transfer and storage organization for a MAP turbo decoder module

Abstract

Turbo codes are the most recent breakthrough in coding theory. Although their decoding algorithm is highly data dominated, no systematic memory optimization study has been performed yet. We have applied the IMEC Data Transfer and Storage Exploration (DTSE) methodology to the MAP (Maximum A Posteriori) class of turbo decoding algorithms. We present an extensive overview of our optimizations and tradeoffs, which result in a parametric family of new optimized algorithms. The optimal choice of parameters depends on the specific turbo code and on the implementation target, which can be either hardware or software.