Iterative Threshold Decoding of Spatially Coupled, Parallel-Concatenated Codes

Spatially coupled, parallel concatenated codes (SC-PCCs) have been shown to approach channel capacity when decoded using optimal iterative methods. However, under complexity constraints such decoding strategies can result in unacceptable power and latency costs. In this work, we employ convolutional...

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Bibliographic Details
Published in:arXiv.org 2021-09
Main Authors: Cummins, Andrew D, Mitchell, David G M, Costello, Daniel J, Jr
Format: Article
Language:English
Subjects:
Channel capacity
Codes
Complexity
Concatenated codes
Decoders
Decoding
Iterative methods
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Summary:Spatially coupled, parallel concatenated codes (SC-PCCs) have been shown to approach channel capacity when decoded using optimal iterative methods. However, under complexity constraints such decoding strategies can result in unacceptable power and latency costs. In this work, we employ convolutional self-orthogonal component codes along with low-complexity, suboptimal a posteriori probability (APP) threshold decoders with SC-PCCs to reduce decoding complexity. The proposed code design is faster, more energy efficient, and easier to implement than optimal methods, while offering significant coding gain over existing threshold decodable, turbo-like constructions of similar latency and complexity. The design also serves to further illustrate the advantages spatial coupling can provide to existing code constructions and decoder implementations.
ISSN:2331-8422