An Efficient Short High-Order Non-Binary LDPC Decoder Architecture Using a Message-Adaptation EMS Algorithm

Abstract

Short non-binary (NB) low-density parity-check (LDPC) codes provide excellent error rate performance compared to their binary counterparts. This paper presents an efficient layered decoder architecture for short high-order non-binary LDPC codes. A hardware-friendly message-adaptation extended Min-Sum (MA-EMS) algorithm is proposed, where a variety of truncation sizes and message compressions are used, such that the number of decoding cycles and the storage requirements can be reduced. A configurable design that supports a variety of truncation sizes is also proposed such that the hardware efficiency can be significantly increased. An early termination (ET) scheme is used so as to decrease the required number of decoding cycles. These techniques can greatly reduce the complexity of the decoder with almost no loss in performance. To demonstrate these techniques, a (64, 32) 256-ary LDPC decoder is implemented in a 90 nm process, which can provide a throughput of 322.9 Mbps and occupies an area of 6.74 mm 2 . The proposed MA-EMS decoder is able to achieve a similar error-rate performance and a much better area efficiency compared to the original EMS decoder.INDEX TERMS Non-binary low-density parity-check (NB-LDPC) codes, message-adaptation extended min-sum (MA-EMS) algorithm, layered decoding, early termination (ET), very large scale integration (VLSI) architecture.

Ultra-High-Throughput EMS NB-LDPC Decoder with Full-Parallel Node Processing

“…In NB-LDPC decoders, the direct application of the Belief Propagation (BP) [5] algorithm leads to O(q 2 ) complexity and is thus prohibitive for q > 16 . A considerable amount of work has then been dedicated to reduce the complexity of decoding algorithms and their associated architectures ( [6][7][8][9][10][11], among others), with a special focus on the Check Node (CN) processing which is the major bottleneck in NB-LDPC decoders. This work particularly focuses on the Extended Min-Sum (EMS) algorithm [12,13] as it currently continues to present one of the most competitive complexity/performance trade-offs [14,15].…”