A Novel Scheme for Peak-to-Average Power Ratio Reduction Using Polar Codes

Chin Chieh Huang, Tzu Chieh Kao, Cheng Yu Pai, Chao Yu Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, a novel scheme based on polar codes is presented to deal with the high peak-to-average power ratio (PAPR) problem in the orthogonal frequency division multiplexing (OFDM) system. The proposed method uses the frozen bits in polar codes to generate an offset. Then, the offset is added to the encoded codeword such that the transmitted codeword can have a lower PAPR. Also, an algorithm is proposed to find the appropriate combination of frozen bits for a given dimension and a codeword length. In some cases, the transmitted codeword lies in a certain Golay complementary set (GCS). Therefore, the transmitted codeword has upper-bounded PAPRs due to the well-known PAPR property of the GCS. In comparison with the selected mapping (SLM) scheme, the proposed scheme has lower computational complexity since the values of the frozen bits are determined in advance. Simulation results show that the proposed algorithm offers good PAPR reduction without affecting the decoding performance of the polar code.

Original languageEnglish
Title of host publication2022 10th International Workshop on Signal Design and Its Applications in Communications, IWSDA 2022 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665452984
DOIs
Publication statusPublished - 2022
Event10th International Workshop on Signal Design and Its Applications in Communications, IWSDA 2022 - Colchester, United Kingdom
Duration: 2022 Aug 12022 Aug 5

Publication series

Name2022 10th International Workshop on Signal Design and Its Applications in Communications, IWSDA 2022 - Proceedings

Conference

Conference10th International Workshop on Signal Design and Its Applications in Communications, IWSDA 2022
Country/TerritoryUnited Kingdom
CityColchester
Period22-08-0122-08-05

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Signal Processing

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