电讯技术2017，Vol.57Issue(7)：741-744,4.DOI:10.3969/j.issn.1001-893x.2017.07.001
应用深度学习的信号解调
Demodulation with Deep Learning
摘要
Abstract
This paper proposes a deep learning based demodulation method by identifying the modulated signal in radio channel.The proposed deep belief network is composed of multilayer restricted Boltzmann machines.The communication signal is transformed into a new form,which is used as the input of the deep belief network and system training.The deep belief network extracts the characteristics of communication signals by top-down depth learning and bottom-up feedback fine tuning.The algorithm's practicability is verified by simulation.The simulation also indicates that the bit error rate(BER) of the proposed method is almost 0.4 dB better than that of traditional one.关键词
无线通信/信号解调/深度学习/深层置信网络/信号识别Key words
wireless communication/demodulation/deep learning/deep belief network/signal identification分类
信息技术与安全科学引用本文复制引用
黄媛媛,张剑,周兴建,卢建川..应用深度学习的信号解调[J].电讯技术,2017,57(7):741-744,4.基金项目
国防重点实验室基金项目(9140C020203150C02008) （9140C020203150C02008）
