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Optics Express
Article . 2023 . Peer-reviewed
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Low-complexity LDPC decoding algorithms for ultra-high-order modulated signals

Authors: Hongjun, Zhu; Meiyu, Fu; Chen, Hou; Guijun, Hu;

Low-complexity LDPC decoding algorithms for ultra-high-order modulated signals

Abstract

Low-complexity decoding algorithms and ultra-high-order modulation formats are necessary to meet data rate requirements in excess of 1 Tbps. The information bottleneck algorithm has been effectively applied to the LDPC decoding algorithm in recent years, and its performance is comparable to that of the double-precision information propagation technique. However, the application of information bottleneck decoding algorithms in ultra-high order modulation forms has received little attention. Furthermore, the number of table lookups required for a single decoding loop is square to the node degree, which is undesirable for optical communications. We present a low-complexity LDPC decoding technique for ultra-high-order modulated signals in this study. First, the algorithm employs multivariate covariates to build an information bottleneck framework, which introduces the processing required for applying the information bottleneck algorithm to 1024-QAM signals and the requirement of combining higher-order modulation formats with LDPC codes. The technique makes use of a bidirectional recursive network and the symmetry of quantized information to reuse the same set of tables, considerably reducing the number of table lookup operations required in the decoding process. Constructing a coherent optical communication system with 1024-QAM signals proves that the proposed algorithm can operate effectively. The performance sacrifice of 0.2 ∼ 0.3 dB reduces the number of table lookup operations required for decoding from square to linear magnitude, which greatly reduces the decoding time required in optical communication.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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