POLAR CODES WITH ENHANCED MACHINE LEARNING
PosterAuthor:Altmayer, Kumud, PV-Summer & Spec Acad Progs Engineering Grad Non-DegreeUniversity of Virginia
Abstract:
Arikan (2009) introduced a revolutionary approach to achieving capacity on binary memoryless channels,
known as polar coding. The list decoding, particularly accompanied by use of CRC outer code, gives dramatic improvement in block error and bit error probabilities. We look for managing performance across varying signal-to-noise ratios (SNR), for digital wireless communication system.
Machine learning presents a promising solution to develop more robust and intelligent decoding strategies.
We study and do the comparison of traditional and Machine Learning Performance with Polar codes.
Keywords:
5G, 6G, Wireless Digital
5G, 6G, Wireless Digital
Rights:
All rights reserved (no additional license for public reuse)
All rights reserved (no additional license for public reuse)
Contributor:Altmayer, Kumud, PV-Summer & Spec Acad Progs Engineering Grad Non-DegreeUniversity of Virginia
Language:
English
English
Source Citation:
Not published yet.
Publisher:
University of Virginia
University of Virginia
Published Date:
in progress.
in progress.
Notes:
It's a poster presentation and publication work is in progress.
