학술논문
Guessing Random Additive Noise Decoding with Quantized Soft Information
Document Type
Conference
Source
2023 IEEE Globecom Workshops (GC Wkshps) Globecom Workshops (GC Wkshps), 2023 IEEE. :1698-1703 Dec, 2023
Subject
Language
Abstract
In this work, we introduce discretized soft GRAND (DS-GRAND) based on dynamic programming (DP), which utilizes quantized soft information. Typical quantization values for per-information bit soft information in decoding chips range from 3 to 5 bits. Our simulations indicate that DSGRAND performs within 0.25 dB and 0.1 dB of maximum-likelihood (ML) decoding with 2 and 3 bit soft information quantizers, respectively. We analyze the memory requirements and computational complexity of DSGRAND, demonstrating that for the CA-SCL Polar decoder with a list size of 128, which closely approaches DSGRAND performance, DSGRAND outperforms CA-SCL by an order of magnitude in time complexity and two orders of magnitude in space complexity.