60 citations · 201 across the 42 of their papers we have counts for
45 papers
Single-Model Adaptive Wireless Image Transmission via Feature Sparsity Regularization
Xianghao Cui, Li Lan, Qi He +4
Learned joint source-channel coding (JSCC) enables robust wireless image transmission by jointly optimizing the transmitter and receiver over differentiable channel models. For ban…
Bridging the Cognitive Gap: A Unified Memory Paradigm for 6G Agentic AI-RAN
Xijun Wang, Zhaoyang Liu, Chenyuan Feng +3
As 6G evolves, the radio access network must transcend traditional automation to embrace agentic AI capable of perception, reasoning, and evolution. A fundamental cognitive gap per…
Accelerating Wireless Distributed Learning via Hybrid Split and Federated Learning Optimization
Kun Guo, Xuefei Li, Xijun Wang +3
Federated learning (FL) and split learning (SL) are two effective distributed learning paradigms in wireless networks, enabling collaborative model training across mobile devices w…
Analysis of SINR Coverage in LEO Satellite Networks through Spatial Network Calculus
Yuting Tang, Yufan He, Yi Zhong +3
We introduce a new analytical framework, developed based on the spatial network calculus, for performance assessment of Low Earth Orbit (LEO) satellite networks. Specifically, we m…
Towards Secure Semantic Transmission In the Era of GenAI: A Diffusion-based Framework
Boxiang He, Zihan Chen, Junshan Luo +4
Semantic communication, due to its focus on the transmitting meaning rather than the raw bit data, poses unique security challenges compared to the traditional communication system…
Diffusion-enabled Secure Semantic Communication Against Eavesdropping
Boxiang He, Zihan Chen, Fanggang Wang +3
In this paper, AN is introduced into semantic communication systems for the first time to prevent semantic eavesdropping. However, the introduction of AN also poses challenges for…
Task-oriented Age of Information for Remote Inference with Hybrid Language Models
Shuying Gan, Xijun Wang, Chenyuan Feng +4
Large Language Models (LLMs) have revolutionized the field of artificial intelligence (AI) through their advanced reasoning capabilities, but their extensive parameter sets introdu…
Take What You Need: Flexible Multi-Task Semantic Communications with Channel Adaptation
Xiang Chen, Shuying Gan, Chenyuan Feng +2
The growing demand for efficient semantic communication systems capable of managing diverse tasks and adapting to fluctuating channel conditions has driven the development of robus…
Analysis of Age of Information for A Discrete-Time hybrid Dual-Queue System
Zhengchuan Chen, Yi Qu, Nikolaos Pappas +3
Using multiple sensors to update the status process of interest is promising in improving the information freshness. The unordered arrival of status updates at the monitor end pose…
Decentralized Semantic Communication and Cooperative Tracking Control for a UAV Swarm over Wireless MIMO Fading Channels
Minjie Tang, Chenyuan Feng, Tony Q. S. Quek
This paper investigates the semantic communication and cooperative tracking control for an UAV swarm comprising a leader UAV and a group of follower UAVs, all interconnected via un…
Robust Federated Learning Over the Air: Combating Heavy-Tailed Noise with Median Anchored Clipping
Jiaxing Li, Zihan Chen, Kai Fong Ernest Chong +3
Leveraging over-the-air computations for model aggregation is an effective approach to cope with the communication bottleneck in federated edge learning. By exploiting the superpos…
Trustworthy Image Semantic Communication with GenAI: Explainablity, Controllability, and Efficiency
Xijun Wang, Dongshan Ye, Chenyuan Feng +3
Image semantic communication (ISC) has garnered significant attention for its potential to achieve high efficiency in visual content transmission. However, existing ISC systems bas…
Spectral Co-Distillation for Personalized Federated Learning
Zihan Chen, Howard H. Yang, Tony Q. S. Quek +1
Personalized federated learning (PFL) has been widely investigated to address the challenge of data heterogeneity, especially when a single generic model is inadequate in satisfyin…
Optimal Status Updates for Minimizing Age of Correlated Information in IoT Networks with Energy Harvesting Sensors
Chao Xu, Xinyan Zhang, Howard H. Yang +4
Many real-time applications of the Internet of Things (IoT) need to deal with correlated information generated by multiple sensors. The design of efficient status update strategies…
Analysis of Age of Information in Non-terrestrial Networks
Yanwu Lu, Howard Yang, Nikolaos Pappas +3
Non-terrestrial networks (NTN), particularly low Earth orbit (LEO) satellite networks, have emerged as a promising solution to overcome the limitations of traditional terrestrial n…
Toward 6G Native-AI Network: Foundation Model based Cloud-Edge-End Collaboration Framework
Xiang Chen, Zhiheng Guo, Xijun Wang +5
Future wireless communication networks are in a position to move beyond data-centric, device-oriented connectivity and offer intelligent, immersive experiences based on multi-agent…
The Role of Federated Learning in a Wireless World with Foundation Models
Zihan Chen, Howard H. Yang, Y. C. Tay +2
Foundation models (FMs) are general-purpose artificial intelligence (AI) models that have recently enabled multiple brand-new generative AI applications. The rapid advances in FMs…
Edge Intelligence Over the Air: Two Faces of Interference in Federated Learning
Zihan Chen, Howard H. Yang, Tony Q. S. Quek
Federated edge learning is envisioned as the bedrock of enabling intelligence in next-generation wireless networks, but the limited spectral resources often constrain its scalabili…
Analysis of the Age of Information in Age-Threshold Slotted ALOHA
Howard H. Yang, Nikolaos Pappas, Tony Q. S. Quek +1
We investigate the performance of a random access network consisting of source-destination dipoles. The source nodes transmit information packets to their destinations over a share…
CoMP Transmission in Downlink NOMA-Based Cellular-Connected UAV Networks
Hongguang Sun, Linyi Zhang, Tony Q. S. Quek +2
In this paper, we study the integration between the coordinated multipoint (CoMP) transmission and the non-orthogonal multiple access (NOMA) in the downlink cellular-connected UAV…
DPP-based Client Selection for Federated Learning with Non-IID Data
Yuxuan Zhang, Chao Xu, Howard H. Yang +2
This paper proposes a client selection (CS) method to tackle the communication bottleneck of federated learning (FL) while concurrently coping with FL's data heterogeneity issue. S…
Hierarchical Personalized Federated Learning Over Massive Mobile Edge Computing Networks
Chaoqun You, Kun Guo, Howard H. Yang +1
Personalized Federated Learning (PFL) is a new Federated Learning (FL) paradigm, particularly tackling the heterogeneity issues brought by various mobile user equipments (UEs) in m…
Personalizing Federated Learning with Over-the-Air Computations
Zihan Chen, Zeshen Li, Howard H. Yang +1
Federated edge learning is a promising technology to deploy intelligence at the edge of wireless networks in a privacy-preserving manner. Under such a setting, multiple clients col…
Understanding the Gain of Deploying IRSs in Large-scale Heterogeneous Cellular Networks
Hu Cheng, Hongguang Sun, Linyi Zhang +3
As the superior improvement on wireless network coverage, spectrum efficiency and energy efficiency, Intelligent reflecting surface (IRS) has received more and more attention. In t…