75 citations · 86 across the 5 of their papers we have counts for
11 papers
Deep Transfer Clustering of Radio Signals
Qi Xuan, Xiaohui Li, Zhuangzhi Chen +3
Modulation recognition is an important task in radio signal processing. Most of the current researches focus on supervised learning. However, in many real scenarios, it is difficul…
GGT: Graph-Guided Testing for Adversarial Sample Detection of Deep Neural Network
Zuohui Chen, Renxuan Wang, Jingyang Xiang +5
Deep Neural Networks (DNN) are known to be vulnerable to adversarial samples, the detection of which is crucial for the wide application of these DNN models. Recently, a number of…
Adaptive Visibility Graph Neural Network and its Application in Modulation Classification
Qi Xuan, Kunfeng Qiu, Jinchao Zhou +4
Our digital world is full of time series and graphs which capture the various aspects of many complex systems. Traditionally, there are respective methods in processing these two d…
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…