PAPR reduction of OFDM signals using radial basis function neural networks

Insoo Sohn, Shin Jaeho

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

1 Scopus citations

Abstract

In this paper we investigate a novel peak-to-average power ratio (PAPR) reduction method based on radial basis function network (RBFN). The RBFN can be regarded as a method of adaptive curve-fitting interpolator and is used to generate optimum mapping pattern to reduce the PAPR in this paper. Our simulation results show that our proposed method has significant performance advantages with low computational complexity compared to the conventional methods.

Original languageEnglish
Title of host publication2006 International Conference on Communication Technology, ICCT '06
DOIs
StatePublished - 2006
Event2006 International Conference on Communication Technology, ICCT '06 - Guilin, China
Duration: 27 Nov 200630 Nov 2006

Publication series

NameInternational Conference on Communication Technology Proceedings, ICCT

Conference

Conference2006 International Conference on Communication Technology, ICCT '06
Country/TerritoryChina
CityGuilin
Period27/11/0630/11/06

Keywords

  • OFDM
  • PAPR
  • RBF

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