3 citations · 5 across the 8 of their papers we have counts for
5 papers · 1 filter
Generalized Segmented GRAND for Guesswork Reduction in Turbo Product Decoding
Lukas Rapp, Jiewei Feng, Muriel Médard +1
Guessing random additive noise decoding (GRAND) can efficiently decode any moderately redundant code with near maximum likelihood (ML) performance via noise effect guessing. For bi…
SOGRAND decoding of LDPC codes
Ken R. Duffy, Jiewei Feng, Lukas Rapp +1
Long forward error correction codes are typically constructed by concatenating shorter component codes that are then decoded through iterative Soft-Input Soft-Output (SISO) of thei…
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…
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…