Architecture and VLSI realization of a high-speed programmable decoder for LDPC convolutional codes

Abstract

In this paper, we present a novel high-speed dual-core programmable decoder architecture for LDPC convolutional codes and their tail-biting versions. This architecture uses a modified Min-Sum algorithm and enables the decoding of a multitude of codes with different node degree distributions, rates and block lengths. We show how the parallelization concepts are derived using the properties of the bipartite graphs underlying the codes. Moreover, the hardware elements composing the architecture will be presented and analyzed in detail. The programmability of the decoder is also considered. Finally, we present the synthesis results for a prototype ASIC which is capable of achieving high decoding throughput still with very high flexibility, relatively low power consumption and small area.