Logarithmic Non-uniform Quantization for List Decoding of Polar Codes

Mohammad Rowshan, Emanuele Viterbo, Rino Micheloni, Alessia Marelli

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The quantization of intermediate log-likelihood ratios (LLRs) is a concern in the hardware implementation of the LLR-based tree search algorithms such as successive cancellation list (SCL) and sequential (SCS) decoding for polar codes (particularly for large block-lengths), where comparability of tree paths requires precision for path metrics that the uniform quantization demands a large memory space due to the wide dynamic range. As the consequence of low accuracy in uniform quantization (with large step size) for small LLR values, the error correction performance degrades. In this work, we present a logarithmic non-uniform quantization (based on lookup table, logarithm functions, and piecewise linear functions) which can provide an error correction performance close to floating-point precision for a wide range of code-lengths.

Original languageEnglish
Title of host publication2021 IEEE 11th Annual Computing and Communication Workshop and Conference (CCWC)
EditorsRajashree Paul
Place of PublicationPiscataway NJ USA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Number of pages6
ISBN (Electronic)9780738143941, 9781665414906
ISBN (Print)9781665430586
Publication statusPublished - 2021
EventIEEE Annual Computing and Communication Workshop and Conference 2021 - Online, Las Vegas, United States of America
Duration: 27 Jan 202130 Jan 2021
Conference number: 11th
https://ieeexplore-ieee-org.ezproxy.lib.monash.edu.au/xpl/conhome/9375825/proceeding (Proceedings)
https://ieee-ccwc.org (Website)


ConferenceIEEE Annual Computing and Communication Workshop and Conference 2021
Abbreviated titleCCWC 2021
Country/TerritoryUnited States of America
CityLas Vegas
Internet address


  • list decoding
  • Polar codes
  • quantization
  • sequential decoding
  • successive cancellation

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