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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

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

Proposals have been made to reduce the guesswork of Guessing Random Additive Noise Decoding (GRAND) for binary linear codes by leveraging codebook structure at the expense of degraded block error rate (BLER). We establish one can preserve…

Information Theory · Computer Science 2025-12-18 Lukas Rapp , Muriel Médard , Ken R. Duffy

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

Guessing Random Additive Noise Decoding (GRAND) is a recently proposed universal Maximum Likelihood (ML) decoder for short-length and high-rate linear block-codes. Soft-GRAND (SGRAND) is a prominent soft-input GRAND variant, outperforming…

Information Theory · Computer Science 2022-12-05 Syed Mohsin Abbas , Marwan Jalaleddine , Warren J. Gross

Guessing random additive noise decoding (GRAND) is a recently proposed decoding paradigm particularly suitable for codes with short length and high rate. Among its variants, ordered reliability bits GRAND (ORBGRAND) exploits soft…

Information Theory · Computer Science 2024-04-30 Li Wan , 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

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

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

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

Random jammers that overpower transmitted signals are a practical concern for many wireless communication protocols. As such, wireless receivers must be able to cope with standard channel noise and jamming (intentional or unintentional). To…

Information Theory · Computer Science 2023-01-25 Furkan Ercan , Kevin Galligan , David Starobinski , Muriel Medard , Ken R. Duffy , Rabia Tugce Yazicigil

Guessing Random Additive Noise Decoding (GRAND) is a universal framework for decoding all block codes by testing candidate error patterns (EPs). Ordered Reliability Bits GRAND (ORBGRAND) facilitates parallel implementation of GRAND by…

Information Theory · Computer Science 2026-02-03 Li Wan , Wenyi Zhang

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…

Information Theory · Computer Science 2022-12-20 Mengxiao Liu , Yuejun Wei , Zhenyuan Chen , Wenyi Zhang

CRC codes have long since been adopted in a vast range of applications. The established notion that they are suitable primarily for error detection can be set aside through use of the recently proposed Guessing Random Additive Noise…

Information Theory · Computer Science 2024-10-28 Wei An , Muriel Médard , Ken R. Duffy

The design and implementation of error correcting codes has long been informed by two fundamental results: Shannon's 1948 capacity theorem, which established that long codes use noisy channels most efficiently; and Berlekamp, McEliece, and…

Information Theory · Computer Science 2024-10-30 Ken R. Duffy , Muriel Médard , Wei An

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

We establish that a large, flexible class of long, high redundancy error correcting codes can be efficiently and accurately decoded with guessing random additive noise decoding (GRAND). Performance evaluation demonstrates that it is…

Information Theory · Computer Science 2025-12-18 Peihong Yuan , Muriel Medard , Kevin Galligan , Ken R. Duffy

This paper considers a transmitter, which uses random linear coding (RLC) to encode data packets. The generated coded packets are broadcast to one or more receivers. A receiver can recover the data packets if it gathers a sufficient number…

Information Theory · Computer Science 2022-05-05 Ioannis Chatzigeorgiou

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

Quantum error correction codes (QECCs) play a central role in both quantum communications and quantum computation. Practical quantum error correction codes, such as stabilizer codes, are generally structured to suit a specific use, and…

Quantum Physics · Physics 2023-10-30 Diogo Cruz , Francisco A. Monteiro , Bruno C. Coutinho