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Guessing random additive noise decoding (GRAND) has received widespread attention recently, and among its variants, ordered reliability bits GRAND (ORBGRAND) is particularly attractive due to its efficient utilization of soft information…

Information Theory · Computer Science 2024-04-30 Zhuang Li , Wenyi Zhang

Parallelism has become a central concern in modern decoding frameworks aiming to meet stringent throughput and latency requirements. Guessing Random Additive Noise Decoding (GRAND) is a recently proposed decoding paradigm that tests…

Information Theory · Computer Science 2026-05-04 Li Wan , Huarui Yin , Wenyi Zhang

The high computational cost of approaching the performance of Maximum-likelihood (ML) decoding has limited its practical use for decades. Because the complexity grows exponentially with the message length, researchers have spent years…

Signal Processing · Electrical Eng. & Systems 2026-04-21 Marwan Jalaleddine , Jiajie Li , Syed Mohsin Abbas , Warren J. Gross

To facilitate applications in IoT, 5G, and beyond, there is an engineering need to enable high-rate, low-latency communications. Errors in physical channels typically arrive in clumps, but most decoders are designed assuming that channels…

Information Theory · Computer Science 2023-04-18 Wei An , Muriel Médard , Ken R. Duffy

Future beyond-5G and 6G systems demand ultra-reliable, low-latency communication with short blocklengths, motivating the development of universal decoding algorithms. Guessing decoding, which infers the noise or codeword candidate in order…

Information Theory · Computer Science 2025-11-24 Qianfan Wang , Jifan Liang , Peihong Yuan , Ken R. Duffy , Muriel Médard , Xiao Ma

This paper considers the problem of channel coding over Gaussian intersymbol interference (ISI) channels with a given metric decoding rule. Specifically, it is assumed that the mismatched decoder has an incorrect assumption on the impulse…

Information Theory · Computer Science 2017-06-20 Wasim Huleihel , Salman Salamatian , Neri Merhav , Muriel Médard

Inter symbol interference (ISI), which occurs in a wide variety of channels, is a result of time dispersion. It can be mitigated by equalization, which results in noise coloring. Inspired by the development of Approximate Independence in…

Signal Processing · Electrical Eng. & Systems 2026-05-08 Ken R. Duffy , Moritz Grundei , Jane A. Millward , Muralidhar Rangaswamy , Muriel Medard

In this work, we investigate guessing random additive noise decoding (GRAND) with quantized soft input. First, we analyze the achievable rate of ordered reliability bits GRAND (ORBGRAND), which uses the rank order of the reliability as…

Information Theory · Computer Science 2022-11-28 Peihong Yuan , Ken R. Duffy , Evan P. Gabhart , Muriel Médard

Guessing Random Additive Noise Decoding (GRAND) is a family of universal decoding algorithms suitable for decoding any moderate redundancy code of any length. We establish that, through the use of list decoding, soft-input variants of GRAND…

Information Theory · Computer Science 2022-08-10 Kevin Galligan , Muriel Médard , Ken R. Duffy

A universal decoding procedure is proposed for the intersymbol interference (ISI) Gaussian channels. The universality of the proposed decoder is in the sense of being independent of the various channel parameters, and at the same time,…

Information Theory · Computer Science 2014-03-18 Wasim Huleihel , Neri Merhav

We present a novel method for error correction in the presence of fading channel estimation errors (CEE). When such errors are significant, considerable performance losses can be observed if the wireless transceiver is not adapted. Instead…

Information Theory · Computer Science 2025-06-18 Charles Wiame , Ken R. Duffy , Muriel Médard

Within the family of guessing-based decoding algorithms, ordered reliability bits GRAND (ORBGRAND) has attracted considerable attention due to its efficient use of soft information and suitability for hardware implementation. It has also…

Information Theory · Computer Science 2026-05-05 Zhuang Li , Wenyi Zhang

There have been significant advances in recent years in the development of forward error correction decoders that can decode codes of any structure, including practical realizations in synthesized circuits and taped out chips. While…

Signal Processing · Electrical Eng. & Systems 2025-11-11 Jiewei Feng , Ken R. Duffy , Muriel Médard

Maximum-likelihood (ML) decoding can be used to obtain the optimal performance of error correction codes. However, the size of the search space and consequently the decoding complexity grows exponentially, making it impractical to be…

Information Theory · Computer Science 2022-05-25 Mohammad Rowshan , Jinhong Yuan

Modern applications are driving demand for ultra-reliable low-latency communications, rekindling interest in the performance of short, high-rate error correcting codes. To that end, here we introduce a soft-detection variant of Guessing…

Information Theory · Computer Science 2021-06-16 Ken R. Duffy

Inter-symbol interference (ISI) channels with data dependent Gauss Markov noise have been used to model read channels in magnetic recording and other data storage systems. The Viterbi algorithm can be adapted for performing maximum…

Information Theory · Computer Science 2010-06-28 Naveen Kumar , Aditya Ramamoorthy , Murti Salapaka

Error correction techniques traditionally focus on the co-design of restricted code-structures in tandem with code-specific decoders that are computationally efficient when decoding long codes in hardware. Modern applications are, however,…

Information Theory · Computer Science 2022-10-12 Ken R. Duffy , Wei An , Muriel Medard

Ultra-reliable low-latency communication (URLLC), a major 5G New-Radio use case, is the key enabler for applications with strict reliability and latency requirements. These applications necessitate the use of short-length and high-rate…

Information Theory · Computer Science 2022-03-14 Syed Mohsin Abbas , Thibaud Tonnellier , Furkan Ercan , Marwan Jalaleddine , Warren J. Gross

The ordered-reliability bits (ORB) variant of guessing random additive noise decoding (GRAND), known as ORBGRAND, achieves remarkably low time complexity at high code rates compared to other GRAND variants. However, its computational…

Information Theory · Computer Science 2025-02-05 Mohammad Rowshan , Jinhong Yuan

We introduce a novel approach to error correction decoding in the presence of additive alpha-stable noise, which serves as a model of interference-limited wireless systems. In the absence of modifications to decoding algorithms, treating…

Information Theory · Computer Science 2024-10-31 Charles Wiame , Ken R. Duffy , Muriel Médard