Polar codes based OFDM-PLC systems in the presence of middleton class-A noise

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

23 Scopus citations

Abstract

The performance of power line communication (PLC) systems suffer mainly from non-Gaussian noise, commonly referred to as impulsive noise. To reduce the effect of this noise, various channel coding techniques have been studied in the literature over PLC channels. Unlike existing works, in this paper we investigate the performance and robustness of polar codes over impulsive noise PLC channels for different codeword lengths and noise scenarios in orthogonal frequency division multiplexing (OFDM) systems. In particular, insightful comparisons between hard decision (HD) decoding and soft decision (SD) decoding for the proposed system are made. Furthermore, we investigate the blanking and clipping techniques with polar codes for impulsive noise mitigation. In addition, for the sake of comparison, results for LDPC coding are also presented. The results show that polar codes can considerably improve the performance of PLC systems. It will also be demonstrated that SD decoding offers better performance than HD decoding and that as the codeword length is increased, the performance can be further improved.

Original languageEnglish
Title of host publication2016 10th International Symposium on Communication Systems, Networks and Digital Signal Processing, CSNDSP 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509025268
DOIs
StatePublished - 21 Sep 2016
Externally publishedYes

Publication series

Name2016 10th International Symposium on Communication Systems, Networks and Digital Signal Processing, CSNDSP 2016

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

Keywords

  • Impulsive noise
  • orthogonal frequency division multiplexing (OFDM)
  • polar codes
  • power line communications (PLC)

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Signal Processing

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