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A Low-Complexity Decoder With Non-Uniform Quantization for Recursive BMST Codes

Authors: Shengbo Ai; Shancheng Zhao;

A Low-Complexity Decoder With Non-Uniform Quantization for Recursive BMST Codes

Abstract

Recursive block Markov superposition transmission (rBMST) can be used to construct high-performance spatially coupled codes. When used in power-limited scenarios, low-complexity quantized decoders are required for the rBMST codes. In this letter, we introduce an efficient decoder for rBMST codes by incorporating non-uniform quantization (NUQ) into the threshold attenuated min-sum algorithm (TAMSA). The resulting decoder is referred to as the NUQ-TAMSA. We use the hierarchical dynamic quantization algorithm to design the non-uniform quantizer. To show the effectiveness of the NUQ-TAMSA, we carry out comprehensive comparisons. Our results show that, for low-resolution quantization, performance gains as large as 0.3 dB can be obtained with the NUQ-TAMSA. Numerical results also show that, for a wide range of coding rates, 5-bits non-uniform quantization is sufficient for NUQ-TAMSA to approach the performances of the floating-point based TAMSA.

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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!
1
Average
Average
Average
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