An iterative decoding algorithm for channels with gibbs distributed noise
Tadashi Wadayama · 2003
An iterative decoding algorithm suit- able for channels with Gibbs distributed noise is pre- sented. In particular, we focus on the channel with 2- dimensional correlated noise represented by a Markov random field(MRF). I. INTRODUCTION Excellent empirical performance of turbo codes and LDPC codes has inspired researchers to investigate decoding algo- rithms not only for memoryless channels, but also for chan- nels with memory. In this paper, we discuss a channel model with Gibbs distributed noise. The Gibbs distribution which is an exponential-type distribution appears in many fields such as statistical physics, image analysis, neural network etc.. In particular, we here focus on the channels with 2-dimensional correlated noise represented by a Markov random field(MRF). It is known that a joint distribution of any MRF is a Gibbs distribution. A channel with 2-dimensional correlated noise is shown in Fig.1. 2-dimensional correlated noise