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Journal of Signal Processing Systems

GPU Accelerated Belief Propagation Decoding of Non-Binary LDPC Codes with Parallel and Sequential Scheduling

Moritz Beermann, Enrique Monzó, Laurent Schmalen, Peter Vary

Published Aug 21, 2014• 11 citations
Publisher
DOI
10.1007/s11265-014-0927-7

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Non-binary low-density parity-check (LDPC) codes have been shown to attain near capacity error correcting performance in noisy wireless communication channels. It is well known that these codes require a very large number of operations per-bit to decode. This high computational complexity along with a parallel decoder structure makes graphics processing units (GPUs) an attractive platform for acceleration of the decoding algorithm. The seemingly random memory access patterns associated with decoding are generally beneficial to error-correcting performance but present a challenge to designers who want to leverage the computational capabilities of the GPU. In this paper we describe the design of an efficient decoder implementation based on GPUs and a corresponding set of powerful non-binary LDPC codes. Using the belief propagation algorithm with a sequential message updating scheme it is shown that we are able to exploit parallelism inherent in the decoding algorithm while decreasing the number of decoding iterations required for convergence.
The design of LDPC decoders with low complexity, high throughput, and good performance is a critical task. A well-known strategy is to design structured codes such as quasi- cyclic LDPC (QC-LDPC) that allow partially-parallel decoders. Sequential schedules, such as Layered Belief-Propagation (LBP), converge faster than the traditional flooding schedule while allowing parallel decoding of QC-LDPC codes. In this paper, we propose a novel low-complexity sequential schedule called Zigzag LBP (Z-LBP). Current LBP schedules do not allow partially- parallel architectures in the regime of high-rate codes with small- to-medium blocklengths. Our proposed algorithm can still be implemented in a partially-parallel manner in this regime. Z-LBP provides the same benefits as LBP including faster convergence speed and lower frame error rates than flooding.
Low-density parity-check (LDPC) codes have proved to be very powerful channel coding schemes with a broad range of applications. However, as maximum-likelihood decoding is utterly complex, suboptimal decoders have to be employed. One of the most popular decoding algorithms of LDPC codes is belief propagation (BP) decoding. In this paper, we present a novel scheduling for belief propagation decoding of LDPC codes. The new approach combines probabilistic scheduling with the known shuffled and check-shuffled serial scheduling algorithms. The resulting probabilistic shuffled and probabilistic check-shuffled decoders show a superior performance in terms of residual bit error rate. The drawback is that the convergence speed is slightly decreased. However, the convergence is still faster than for the standard and probabilistic flooding algorithms. Furthermore, we have adapted the probabilistic flooding schedule and the proposed probabilistic shuffled schedule to the non-binary case. We show that the aforementioned effects on the binary decoder can similarly be observed when applying the different schedules to the decoding of LDPC codes over higher order Galois fields.