229 citations · 876 across the 52 of their papers we have counts for
40 papers · 1 filter
Soft-output (SO) GRAND and Iterative Decoding to Outperform LDPCs
Peihong Yuan, Muriel Medard, Kevin Galligan +1
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 (GR…
Upgrade error detection to prediction with GRAND
Kevin Galligan, Peihong Yuan, Muriel Médard +1
Guessing Random Additive Noise Decoding (GRAND) is a family of hard- and soft-detection error correction decoding algorithms that provide accurate decoding of any moderate redundan…
Using channel correlation to improve decoding -- ORBGRAND-AI
Ken R. Duffy, Moritz Grundei, Muriel Medard
To meet the Ultra Reliable Low Latency Communication (URLLC) needs of modern applications, there have been significant advances in the development of short error correction codes a…
GRAND-EDGE: A Universal, Jamming-resilient Algorithm with Error-and-Erasure Decoding
Furkan Ercan, Kevin Galligan, David Starobinski +3
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…
Physical layer insecurity
Muriel Médard, Ken R. Duffy
In the classic wiretap model, Alice wishes to reliably communicate to Bob without being overheard by Eve who is eavesdropping over a degraded channel. Systems for achieving that ph…
Soft detection physical layer insecurity
Ken R. Duffy, Muriel Medard
We establish that during the execution of any Guessing Random Additive Noise Decoding (GRAND) algorithm, an interpretable, useful measure of decoding confidence can be evaluated. T…