25 citations · 25 across the 5 of their papers we have counts for
5 papers
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…
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…
A General Security Approach for Soft-information Decoding against Smart Bursty Jammers
Furkan Ercan, Kevin Galligan, Ken R. Duffy +3
Malicious attacks such as jamming can cause significant disruption or complete denial of service (DoS) to wireless communication protocols. Moreover, jamming devices are getting sm…
Block turbo decoding with ORBGRAND
Kevin Galligan, 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, th…