111 citations · 310 across the 38 of their papers we have counts for
39 papers
Deep Learning for Multi-Antenna Modulation Recognition of Radio Signals
Tao Chen, Shilian Zheng, Jiepeng Chen +3
Multi-antenna receiving systems have become a prevalent technical solution in communication systems. Meanwhile, deep learning has achieved significant progress in automatic modulat…
Unsupervised Equivalent Contrastive Learning for Radio Signal Recognition
Shilian Zheng, Jie Chen, Luxin Zhang +1
Robust radio signal recognition is fundamental to spectrum management, electromagnetic space security, and intelligent wireless applications, yet existing deep-learning methods rel…
DS-Pnet: FM-Based Positioning via Downsampling
Shilian Zheng, Xinjiang Qiu, Luxin Zhang +3
In this paper we present DS-Pnet, a novel framework for FM signal-based positioning that addresses the challenges of high computational complexity and limited deployment in resourc…
WK-Pnet: FM-Based Positioning via Wavelet Packet Decomposition and Knowledge Distillation
Shilian Zheng, Quan Lin, Peihan Qi +4
Accurate and efficient positioning in complex environments is critical for applications where traditional satellite-based systems face limitations, such as indoors or urban canyons…
Multi-view Correlation-aware Network Traffic Detection on Flow Hypergraph
Jiajun Zhou, Wentao Fu, Hao Song +2
As the Internet rapidly expands, the increasing complexity and diversity of network activities pose significant challenges to effective network governance and security regulation.…
Reassessing Layer Pruning in LLMs: New Insights and Methods
Yao Lu, Hao Cheng, Yujie Fang +6
Although large language models (LLMs) have achieved remarkable success across various domains, their considerable scale necessitates substantial computational resources, posing sig…
RedTest: Towards Measuring Redundancy in Deep Neural Networks Effectively
Yao Lu, Peixin Zhang, Jingyi Wang +3
Deep learning has revolutionized computing in many real-world applications, arguably due to its remarkable performance and extreme convenience as an end-to-end solution. However, d…
Lateral Movement Detection via Time-aware Subgraph Classification on Authentication Logs
Jiajun Zhou, Jiacheng Yao, Xuanze Chen +3
Lateral movement is a crucial component of advanced persistent threat (APT) attacks in networks. Attackers exploit security vulnerabilities in internal networks or IoT devices, exp…
Rethinking Graph Transformer Architecture Design for Node Classification
Jiajun Zhou, Xuanze Chen, Chenxuan Xie +3
Graph Transformer (GT), as a special type of Graph Neural Networks (GNNs), utilizes multi-head attention to facilitate high-order message passing. However, this also imposes severa…
Photonic time-delayed reservoir computing based on lithium niobate microring resonators
Yuan Wang, Ming Li, Mingyi Gao +5
On-chip micro-ring resonators (MRRs) have been proposed for constructing delay reservoir computing (RC) systems, offering a highly scalable, high-density computational architecture…
MDM: Advancing Multi-Domain Distribution Matching for Automatic Modulation Recognition Dataset Synthesis
Dongwei Xu, Jiajun Chen, Yao Lu +5
Recently, deep learning technology has been successfully introduced into Automatic Modulation Recognition (AMR) tasks. However, the success of deep learning is all attributed to th…
Enhancing Ethereum Fraud Detection via Generative and Contrastive Self-supervision
Chenxiang Jin, Jiajun Zhou, Chenxuan Xie +3
The rampant fraudulent activities on Ethereum hinder the healthy development of the blockchain ecosystem, necessitating the reinforcement of regulations. However, multiple imbalanc…
A Generic Layer Pruning Method for Signal Modulation Recognition Deep Learning Models
Yao Lu, Yutao Zhu, Yuqi Li +4
With the successful application of deep learning in communications systems, deep neural networks are becoming the preferred method for signal classification. Although these models…
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…
Deep Image Semantic Communication Model for Artificial Intelligent Internet of Things
Li Ping Qian, Yi Zhang, Sikai Lyu +4
With the rapid development of Artificial Intelligent Internet of Things (AIoT), the image data from AIoT devices has been witnessing the explosive increasing. In this paper, a nove…
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,…
Can pre-trained models assist in dataset distillation?
Yao Lu, Xuguang Chen, Yuchen Zhang +7
Dataset Distillation (DD) is a prominent technique that encapsulates knowledge from a large-scale original dataset into a small synthetic dataset for efficient training. Meanwhile,…
Photonic time-delayed reservoir computing based on series coupled microring resonators with high memory capacity
Yijia Li, Ming Li, MingYi Gao +7
On-chip microring resonators (MRRs) have been proposed to construct the time-delayed reservoir computing (RC), which offers promising configurations available for computation with…
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…
PathMLP: Smooth Path Towards High-order Homophily
Jiajun Zhou, Chenxuan Xie, Shengbo Gong +4
Real-world graphs exhibit increasing heterophily, where nodes no longer tend to be connected to nodes with the same label, challenging the homophily assumption of classical graph n…
Subgraph Networks Based Contrastive Learning
Jinhuan Wang, Jiafei Shao, Zeyu Wang +3
Graph contrastive learning (GCL), as a self-supervised learning method, can solve the problem of annotated data scarcity. It mines explicit features in unannotated graphs to genera…
Clarify Confused Nodes via Separated Learning
Jiajun Zhou, Shengbo Gong, Xuanze Chen +4
Graph neural networks (GNNs) have achieved remarkable advances in graph-oriented tasks. However, real-world graphs invariably contain a certain proportion of heterophilous nodes, c…
TSGN: Transaction Subgraph Networks Assisting Phishing Detection in Ethereum
Jinhuan Wang, Pengtao Chen, Xinyao Xu +4
Due to the decentralized and public nature of the Blockchain ecosystem, the malicious activities on the Ethereum platform impose immeasurable losses for the users. Existing phishin…
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…