111 citations · 254 across the 13 of their papers we have counts for
13 papers
Deep Learning-Based Frequency Offset Estimation
Tao Chen, Shilian Zheng, Jiawei Zhu +2
In wireless communication systems, the asynchronization of the oscillators in the transmitter and the receiver along with the Doppler shift due to relative movement may lead to the…
Augmenting Radio Signals with Wavelet Transform for Deep Learning-Based Modulation Recognition
Tao Chen, Shilian Zheng, Kunfeng Qiu +3
The use of deep learning for radio modulation recognition has become prevalent in recent years. This approach automatically extracts high-dimensional features from large datasets,…
AIR: Threats of Adversarial Attacks on Deep Learning-Based Information Recovery
Jinyin Chen, Jie Ge, Shilian Zheng +5
A wireless communications system usually consists of a transmitter which transmits the information and a receiver which recovers the original information from the received distorte…
Mixing Signals: Data Augmentation Approach for Deep Learning Based Modulation Recognition
Xinjie Xu, Zhuangzhi Chen, Dongwei Xu +5
With the rapid development of deep learning, automatic modulation recognition (AMR), as an important task in cognitive radio, has gradually transformed from traditional feature ext…
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…
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…
CLPVG: Circular limited penetrable visibility graph as a new network model for time series
Qi Xuan, Jinchao Zhou, Kunfeng Qiu +3
Visibility Graph (VG) transforms time series into graphs, facilitating signal processing by advanced graph data mining algorithms. In this paper, based on the classic Limited Penet…
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…