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PAPR reduction of OFDM signal by neural networks without side information and its FPGA implementation
Author(s) -
Ohta Masaya,
Ueda Yasuo,
Yamashita Katsumi
Publication year - 2008
Publication title -
electronics and communications in japan
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.131
H-Index - 13
eISSN - 1942-9541
pISSN - 1942-9533
DOI - 10.1002/ecj.10081
Subject(s) - orthogonal frequency division multiplexing , transmitter , reduction (mathematics) , field programmable gate array , computer science , signal (programming language) , electronic engineering , companding , vhdl , telecommunications , computer hardware , engineering , mathematics , programming language , channel (broadcasting) , geometry
Abstract A major drawback of orthogonal frequency division multiplexing (OFDM) is the high peak‐to‐average power ratio (PAPR) of the transmitted signal. PAPR reduction techniques by using neural networks have been proposed to reduce the PAPR problem in OFDM transmitter. These techniques require side information to be transmitted from the transmitter to the receiver in order to recover the original data symbol from the receive signal. In this paper, we propose a novel technique to reduce PAPR of OFDM signal. The proposed technique is based on tone injection (TI) and does not use any side information to be transmitted from the transmitter to the receiver. Moreover, the proposed model is designed with VHDL for an FPGA device, and we report evaluation of the performance. © 2008 Wiley Periodicals, Inc. Electron Comm Jpn, 91(4): 52–60, 2008; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/ecj.10081