PAPR and OOBE Suppression of OFDM Signal Using Deep Learning

Orthogonal frequency division multiplexing (OFDM) signals have the characteristics of both high out-of-band emission (OOBE) and high peak-to-average power ratio (PAPR). In this paper, we propose a PAPR reduction method for orthogonal pre-coded OFDM signals with deep learning, called autoencoder, developed recently for image recognition. Numerical experiments showed that the proposed method could reduce the PAPR without any performance degradation in OOBE.