5G NR CA-Polar Maximum Likelihood Decoding by GRAND
Name
1907.01077.pdf
Description
Submitted version
Size
1.82 MB
Format
Unknown
Checksum (MD5)
d21bebde57bf8db68a471d84f98f7d43
Author(s)
Duffy, Ken R.
Solomon, Amit
Konwar, Kishori Mohan
Medard, Muriel
Date Issued
March 2020
Journal
2020 54th Annual Conference on Information Sciences and Systems, CISS 2020
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
2020. "5G NR CA-Polar Maximum Likelihood Decoding by GRAND." 2020 54th Annual Conference on Information Sciences and Systems, CISS 2020.
Version
Original manuscript
Abstract
© 2020 IEEE. CA-Polar codes have been selected for all control channel communications in 5G NR, but accurate, computationally feasible decoders are still subject to development. Here we report the performance of a recently proposed class of optimally precise Maximum Likelihood (ML) decoders, GRAND, that can be used with any block-code. As published theoretical results indicate that GRAND is computationally efficient for short- length, high-rate codes and 5G CA-Polar codes are in that class, here we consider GRAND's utility for decoding them. Simulation results indicate that decoding of 5G CA-Polar codes by GRAND, and a simple soft detection variant, is a practical possibility.
MIT Department
Massachusetts Institute of Technology. Research Laboratory of Electronics
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/CISS48834.2020.1570617412
