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Video s3
    Details
    Author(s)
    Display Name
    Huayi Zhou
    Affiliation
    Affiliation
    McGill University
    Display Name
    Warren Gross
    Affiliation
    Affiliation
    McGill University
    Abstract

    Guessing random additive noise decoding (GRAND) and sphere decoding (SD) are two algorithms that can achieve maximum likelihood decoding. In this paper, a hybrid GRAND-SD (HGRAND) scheme is proposed to extend GRAND to low-rate codes. An accelerated GRAND decoder, assisted by a sphere decoder running in parallel and giving hints to it to allow skipping of certain candidates allows HGRAND to achieve a latency below the minimum latency of the individual component decoders while guaranteeing error-correction performance.