111 citations · 209 across the 6 of their papers we have counts for
6 papers
DemodNet: Learning Soft Demodulation from Hard Information Using Convolutional Neural Network
Shilian Zheng, Xiaoyu Zhou, Shichuan Chen +2
Soft demodulation is a basic module of traditional communication receivers. It converts received symbols into soft bits, that is, log likelihood ratios (LLRs). However, in the noni…
SigNet: A Novel Deep Learning Framework for Radio Signal Classification
Zhuangzhi Chen, Hui Cui, Jingyang Xiang +6
Deep learning methods achieve great success in many areas due to their powerful feature extraction capabilities and end-to-end training mechanism, and recently they are also introd…
DeepReceiver: A Deep Learning-Based Intelligent Receiver for Wireless Communications in the Physical Layer
Shilian Zheng, Shichuan Chen, Xiaoniu Yang
A canonical wireless communication system consists of a transmitter and a receiver. The information bit stream is transmitted after coding, modulation, and pulse shaping. Due to th…
Deep Learning for Cooperative Radio Signal Classification
Shilian Zheng, Shichuan Chen, Xiaoniu Yang
Radio signal classification has a very wide range of applications in cognitive radio networks and electromagnetic spectrum monitoring. In this article, we consider scenarios where…
Spectrum Sensing Based on Deep Learning Classification for Cognitive Radios
Shilian Zheng, Shichuan Chen, Peihan Qi +2
Spectrum sensing is a key technology for cognitive radios. We present spectrum sensing as a classification problem and propose a sensing method based on deep learning classificatio…
Deep Learning for Large-Scale Real-World ACARS and ADS-B Radio Signal Classification
Shichuan Chen, Shilian Zheng, Lifeng Yang +1
Radio signal classification has a very wide range of applications in the field of wireless communications and electromagnetic spectrum management. In recent years, deep learning ha…