電気学会論文誌C(電子・情報・システム部門誌)
Online ISSN : 1348-8155
Print ISSN : 0385-4221
ISSN-L : 0385-4221
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Side Informationを不要とするNeural NetworkによるOFDM信号のPAPR抑圧法とそのハードウェア化
太田 正哉上田 康雄山下 勝己
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2006 年 126 巻 11 号 p. 1296-1303

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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 received signal. In this paper, we propose a novel technique to reduce PAPR of OFDM signal. Proposed technique is based on Tone Injection(TI) and dose not use any side information to be transmitted from the transmitter to the receiver. Moreover, the proposed model is designed with VHDL for a FPGA device, and evaluated the performance.
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© 電気学会 2006
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