Interleaved Noise Recycling using GRAND

IEEE International Conference on Communications (ICC)(2022)

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摘要
Noise recycling is a recently proposed method that significantly enhances decoding performance when used for orthogonal channels impacted by correlated noise with only receiver side changes. In this paper, we establish that noise recycling can be applied in a single communication channel that is subject to temporally correlated noise by leveraging a standard matrix interleaver to create the effect of orthogonal channels. The proposed interleaved noise recycling technique works with any code, requires no sender-side alterations, and only minor changes to the receiver architecture. In a harddetection scenario, we demonstrate noise recycling can enable an accurate estimate of continuous realization of noise without using any soft information, resulting in a gain of more than 2 dB in Block Error Rate (BLER). We use the first hardware implementation of Guessing Random Additive Noise Decoding (GRAND), a universal noise-centric decoder, to illustrate the advantages of noise recycling in hardware performance. At a correlation coefficient of 0.75, E-b/N-0 of 4 dB, a maximum of 36x decoding energy savings with a 12x reduction in latency is achieved using a BCH(127,113) code when GRAND is equipped with the proposed noise recycling.
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关键词
channel decoding,decoder,noise recycling,GRAND,correlated noise
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