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In this paper, we present a linear-time decoding algorithm for expander codes based on irregular graphs of any positive vertex expansion factor [Formula: see text] and inner codes with a minimum distance of at least [Formula: see text], where [Formula: see text] is the maximum right degree. The algorithm corrects a constant fraction of errors. It builds on two thrusts. The first is a series of works starting with that of Sipser and Spielman [Expander codes, IEEE Trans. Inf. Theory 42(6) (1996) 1710–1722] demonstrating that an asymptotically good family of error-correcting codes that can be decoded in linear time even from a constant fraction of errors in a received word provided [Formula: see text] is at least [Formula: see text] and continuing to the results of Gao and Dowling [Fast decoding of expander codes, IEEE Trans. Inf. Theory 64(2) (2018) 972–978], which only require [Formula: see text] provided the inner code minimum distance is sufficiently large. The second is the improved performance of LDPC codes based on irregular graphs demonstrated by Luby et al. [Improved low- density parity-check codes using irregular graphs, IEEE Trans. Inf. Theory 47(2) (2001) 585–598] and Richardson et al. [Design of capacity- approaching irregular low-density parity-check codes, IEEE Trans. Inf. Theory 47(2) (2001) 619–637]. The algorithm presented in this paper allows for irregular or regular graph-based constructions and uses inner codes of appropriate lengths as checks rather than simple parity-checks.
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On the Design of Generalized LDPC Codes with Component BCJR Decoding
Generalized low-density parity-check (GLDPC) codes, where the single parity-check (SPC) nodes are replaced by generalized constraint (GC) nodes, are known to offer a reduced gap to capacity when compared with conventional LDPC codes, while also maintaining linear growth of minimum distance. However, for certain classes of practical GLDPC codes, there remains a gap to capacity even when utilizing blockwise decoding algorithm at GC nodes. In this work, we propose to optimize the design of GLDPC codes where the GC nodes are decoded with a trellis-based bit-wise Bahl-Cocke-Jelinek- Raviv (BCJR) component decoding algorithm. We analyze the asymptotic threshold behavior of GLDPC codes and determine the optimal proportion of the GC nodes in the GLDPC Tanner graph.We show significant performance improvements compared to existing designs with the same order of decoding complexity.
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- Award ID(s):
- 1757207
- PAR ID:
- 10227840
- Date Published:
- Journal Name:
- GLOBECOM 2020 - 2020 IEEE Global Communications Conference
- Page Range / eLocation ID:
- 1 to 6
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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null (Ed.)In this paper, we introduce two new methods of mitigating decoder error propagation for low-latency sliding window decoding (SWD) of spatially coupled low density parity check (SC-LDPC) codes. Building on the recently introduced idea of check node (CN) doping of regular SC-LDPC codes, here we employ variable node (VN) doping to fix (set to a known value) a subset of variable nodes in the coupling chain. Both of these doping methods have the effect of allowing SWD to recover from error propagation, at a cost of a slight rate loss. Experimental results show that, similar to CN doping, VN doping improves performance by up to two orders of magnitude compared to undoped SC-LDPC codes in the typical signal-to-noise ratio operating range. Further, compared to CN doping, VN doping has the advantage of not requiring any changes to the decoding process.In addition, a log-likelihood-ratio based window extension algorithm is proposed to reduce the effect of error propagation. Using this approach, we show that decoding latency can be reduced by up to a significant fraction without suffering any loss in performancemore » « less
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In this paper, we propose a novel message-passing decoding approach that leverages the degeneracy of quantum low-density parity-check codes to enhance decoding performance, eliminating the need for serial scheduling or post-processing. Our focus is on two-block Calderbank-Shor-Steane (CSS) codes, which are composed of symmetric stabilizers that hinder the performance of conventional iterative decoders with uniform update rules. Specifically, our analysis shows that, under the isolation assumption, the min-sum decoder fails to converge when constant-weight errors are applied to symmetric stabilizers, as variable-to-check messages oscillate in every iteration. To address this, we introduce a decoding technique that exploits this oscillatory property by applying distinct update rules: variable nodes in one block utilize messages from previous iterations, while those in the other block are updated conventionally. Logical error-rate results demonstrate that the proposed decoder significantly outperforms the normalized min-sum decoder and achieves competitive performance with belief propagation enhanced by order-zero ordered statistics decoding, all while maintaining linear complexity in the code’s block length.more » « less
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/GLOBECOM42002.2020.9322143
