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发布时间：2020-07-11

论文类型：期刊论文

发表时间：2020-06-01

发表刊物：IEEE COMMUNICATIONS LETTERS

收录刊物：SCIE

卷号：24

期号：6

页面范围：1271-1274

ISSN号：1089-7798

关键字：Peak to average power ratio; Training; Biological neural networks; Neurons; Bandwidth; Feedforward neural network; orthogonal frequency division multiplexing; peak-to-average power ratio; tone reservation

摘要：A major defect of orthogonal frequency division multiplexing (OFDM) systems is the high peak-to-average power ratio (PAPR). In this letter, a novel scheme based on deep leaning, called tone reservation network (TRNet), is proposed for OFDM systems to improve the performance of the tone reservation (TR) technique. More specifically, TRNet reserves a part of tones to generate a peak-canceling signal. The feedforward neural network is used to adaptively generate a peak-canceling signal according to the characteristics of the input signal. Computer simulation results show that the proposed scheme provides a better PAPR reduction performance with fewer reserved tones, which is also beneficial to improve the bandwidth efficiency.