Open AccessRBF Neural Network Based SLM Peak‐to‐Average Power Ratio Reduction in OFDM Systems
Author(s) -
Sohn Insoo
Publication year - 2007
Publication title -
etri journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.295
H-Index - 46
eISSN - 2233-7326
pISSN - 1225-6463
DOI - 10.4218/etrij.07.0206.0155
Subject(s) - orthogonal frequency division multiplexing , reduction (mathematics) , electronic engineering , artificial neural network , power (physics) , function (biology) , phase (matter) , mathematics , algorithm , multiplexing , sequence (biology) , computer science , engineering , telecommunications , artificial intelligence , channel (broadcasting) , physics , geometry , genetics , quantum mechanics , evolutionary biology , biology
One of the major disadvantages of the orthogonal frequency division multiplexing system is high peak‐to‐average power ratio (PAPR). Selected mapping (SLM) is an efficient distortionless PAPR reduction scheme which selects the minimum PAPR sequence from a group of independent phase rotated sequences. However, the SLM requires explicit side information and a large number of IFFT operations. In this letter we investigate a novel PAPR reduction method based on the radial basis function network and SLM.