A Fully Parallel LDPC Decoder Architecture Using Probabilistic Min-Sum Algorithm for High-Throughput Applications

Abstract

This paper presents a normalized probabilistic min-sum algorithm for low-density parity-check (LDPC) codes, where a probabilistic second minimum value, instead of the true second minimum value, is used to facilitate fully parallel decoder realization. The comparators in each check-node unit (CNU) are connected through an interconnect network based on a mix of tree and butterfly networks such that the routing and message passing between the variable-node units (VNUs) and CNUs can be efficiently realized. In order to further reduce the hardware complexity, the normalization operation is realized in the VNU rather than in the CNU. An early termination scheme is proposed in order to prevent unnecessary energy dissipation for both low and high signal-to-noise-ratio regions. The proposed techniques are demonstrated by implementing a (2048, 1723) LDPC decoder using a 90 nm CMOS process. Post-layout simulation results show that the decoder supports a throughput of 45.42 Gbps at 199.6 MHz, achieving the highest throughput and throughput-to-area ratio among comparable works based on a similar or better error performance.