On a New SNR Estimation Approach with Polar Codes

Chaofan Chen, Jiayi Wu, Changhong Wang, Xiaqing Miao, Xiangyuan Bu

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

5 Citations (Scopus)

Abstract

A maximum likelihood polar code-aided (ML-PCA) SNR estimation algorithm is proposed in this paper. In the ML-PCA algorithm, the posterior soft information of polar BP decoding is adopted to help the SNR estimation process. Benefiting from the excellent performance of polar code, the ML-PCA algorithm is able to acquire more reliable decoding information and further improve the SNR estimation quality. By detailed derivation, the SNR estimator and Cramér-Rao Lower Bound (CRLB) of the proposed algorithm are achieved. Numerical simulations demonstrate that the ML-PCA algorithm considerably outperforms the conventional M2M4 and ML-NDA algorithms.

Original languageEnglish
Title of host publicationIMCEC 2021 - IEEE 4th Advanced Information Management, Communicates, Electronic and Automation Control Conference
EditorsBing Xu
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages727-732
Number of pages6
ISBN (Electronic)9781728185347
DOIs
Publication statusPublished - 18 Jun 2021
Event4th IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2021 - Chongqing, China
Duration: 18 Jun 202120 Jun 2021

Publication series

NameIMCEC 2021 - IEEE 4th Advanced Information Management, Communicates, Electronic and Automation Control Conference
ISSN (Print)2693-2814
ISSN (Electronic)2693-2776

Conference

Conference4th IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2021
Country/TerritoryChina
CityChongqing
Period18/06/2120/06/21

Keywords

  • CRLB
  • Signal-to-noise ratio
  • joint estimation
  • maximum likelihood
  • polar codes

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