Modified augmented belief propagation for general memoryless channels.

Abstract

In this paper, we propose an efficient implementation of the augmented belief propagation (ABP) algorithm for low-density parity-check codes over general memoryless channels. ABP is a multistage BP based decoder that uses a backtracking processing when decoding fails. The algorithm proceeds in two main steps, namely a symbol selection step and an augmented decoding step. The former is based on a criterion related both to the stopping subgraph connectivity and to the input reliability, while the latter can be either implemented using a list based or a greedy approach. Compared to the original implementation, we consider a different approach for both steps. First, the proposed node selection is only based on the dynamic of sign changes of the extrinsic messages at the variable nodes output. This enables us to consider indifferently general memoryless channels, while still taking into account the graph irregularity. Then, we propose a simple yet efficient implementation of the augmented decoding procedure based on pruning of the branching tree The proposed algorithm shows near maximum likelihood decoding performance while decreasing the overall complexity (computation and memory) of the original algorithm. Moreover, complexity-performance trade-off is an built-in feature for this kind of algorithm.