13 citations · 19 across the 15 of their papers we have counts for
9 papers · 1 filter
Improving the decoding performance of CA-polar codes
Jiewei Feng, Peihong Yuan, Ken R. Duffy +1
We investigate the use of modern code-agnostic decoders to convert CA-SCL from an incomplete decoder to a complete one. When CA-SCL fails to identify a codeword that passes the CRC…
Guessing Decoding of Short Blocklength Codes
Qianfan Wang, Jifan Liang, Peihong Yuan +3
Future beyond-5G and 6G systems demand ultra-reliable, low-latency communication with short blocklengths, motivating the development of universal decoding algorithms. Guessing deco…
Group Probability Decoding of Turbo Product Codes over Higher-Order Fields
Lukas Rapp, Muriel Médard, Ken R. Duffy
Binary turbo product codes (TPCs) are powerful error-correcting codes constructed from short component codes. Traditionally, turbo product decoding passes log likelihood ratios (LL…
Enhanced GCD through ORBGRAND-AI: Exploiting Partial and Total Correlation in Noise
Jiewei Feng, Ken R. Duffy, Muriel Médard
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 realization…
The Linear Reliability Channel
Alexander Mariona, Ken R. Duffy, Muriel Médard
We introduce and analyze a discrete soft-decision channel called the linear reliability channel (LRC) in which the soft information is the rank ordering of the received symbol reli…
Joint Error Correction and Fading Channel Estimation Enhancement Leveraging GRAND
Charles Wiame, Ken R. Duffy, Muriel Médard
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 o…
SOGRAND Assisted Guesswork Reduction
Lukas Rapp, Muriel Médard, Ken R. Duffy
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 degra…
A Balanced Tree Transformation to Reduce GRAND Queries
Lukas Rapp, Jiewei Feng, Muriel Médard +1
Guessing Random Additive Noise Decoding (GRAND) and its variants, known for their near-maximum likelihood performance, have been introduced in recent years. One such variant, Segme…
Leveraging Code Structure to Improve Soft Output for GRAND, GCD, OSD, and SCL
Jiewei Feng, Ken R. Duffy, Muriel Médard
In addition to a codeword, error correction decoders that provide blockwise soft output (SO) return an estimate of the likelihood that the decoding is correct. Following Forney, su…