Code Rate Optimization via Neural Polar Decoders

Ziv Aharoni, Bashar Huleihel, Henry D. Pfister, Haim H. Permuter

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this work, we explore the enhancement of polar codes for channels with memory, focusing on achieving low decoding complexity and optimizing input distributions for maximum transmission rates. Polar codes are known for their efficient decoding, exhibiting a complexity of O(N log N) in memoryless channels, and complexity of O(|S|3 N log N) in finite state channels (FSCs), where|S|is the state space size. A notable recent advancement is the integration of neural networks (NNs) to create an neural polar decoder (NPD), which is adept at learning from data without the knowledge of the channel model, effectively bypassing the cubic complexity growth associated with the channel state size. In this paper, we propose a framework to optimize the input distribution for polar codes, aiming to maximize the mutual information of effective bit channels. This framework has been tested on both memoryless and FSCs, including the additive white Gaussian noise (AWGN) channel and the Ising channel, yielding promising results. The key contribution of this paper is the demonstration of the feasibility of simultaneously selecting an optimal input distribution and creating a practical decoder for various channel types, even in the absence of a channel model. This approach paves the way for new advancements in data-driven communication theory, especially for channels with memory.

Original languageEnglish
Title of host publication2024 IEEE International Symposium on Information Theory, ISIT 2024 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers
Pages2424-2429
Number of pages6
ISBN (Electronic)9798350382846
DOIs
StatePublished - 1 Jan 2024
Event2024 IEEE International Symposium on Information Theory, ISIT 2024 - Athens, Greece
Duration: 7 Jul 202412 Jul 2024

Publication series

NameIEEE International Symposium on Information Theory - Proceedings
ISSN (Print)2157-8095

Conference

Conference2024 IEEE International Symposium on Information Theory, ISIT 2024
Country/TerritoryGreece
CityAthens
Period7/07/2412/07/24

Keywords

  • Channel capacity
  • channels with memory
  • data-driven
  • polar codes

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Information Systems
  • Modeling and Simulation
  • Applied Mathematics

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