ORBGRAND Is Almost Capacity-Achieving

Decoding via sequentially guessing the error pattern in a received noisy sequence has received attention recently, and ORBGRAND has been proposed as one such decoding algorithm that is capable of utilizing the soft information embedded in the received noisy sequence. An information theoretic study i...

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Bibliographic Details
Published in:IEEE transactions on information theory 2023-05, Vol.69 (5), p.2830-2840
Main Authors: Liu, Mengxiao, Wei, Yuejun, Chen, Zhenyuan, Zhang, Wenyi
Format: Article
Language:English
Subjects:
Achievable rate
Algorithms
AWGN channels
Channel capacity
Codes
Decoding
generalized mutual information
guessing random additive noise decoding
Information theory
mismatched decoding
Noise measurement
ORBGRAND
Random noise
Reliability
Signal to noise ratio
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Summary:Decoding via sequentially guessing the error pattern in a received noisy sequence has received attention recently, and ORBGRAND has been proposed as one such decoding algorithm that is capable of utilizing the soft information embedded in the received noisy sequence. An information theoretic study is conducted for ORBGRAND, and it is shown that the achievable rate of ORBGRAND using independent and identically distributed random codebooks almost coincides with the channel capacity, for an additive white Gaussian noise channel under antipodal input. For finite-length codes, improved guessing schemes motivated by the information theoretic study are proposed that attain lower error rates than ORBGRAND, especially in the high signal-to-noise ratio regime.
ISSN:0018-9448
1557-9654
DOI:10.1109/TIT.2022.3230782