PAPR Reduction of OFDM Signal by Neural Networks without Side Information and Its FPGA Implementation

摘要

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.