74 citations · 366 across the 44 of their papers we have counts for
45 papers
Backdoor Attacks and Defenses on Semantic-Symbol Reconstruction in Semantic Communications
Yuan Zhou, Rose Qingyang Hu, Yi Qian
Semantic communication is of crucial importance for the next-generation wireless communication networks. The existing works have developed semantic communication frameworks based o…
Is the Performance of NOMA-aided Integrated Sensing and Multicast-Unicast Communications Improved by IRS?
Yang Gou, Yinghui Ye, Guangyue Lu +2
In this paper, we consider intelligent reflecting surface (IRS) in a non-orthogonal multiple access (NOMA)-aided Integrated Sensing and Multicast-Unicast Communication (ISMUC) syst…
CSMAAFL: Client Scheduling and Model Aggregation in Asynchronous Federated Learning
Xiang Ma, Qun Wang, Haijian Sun +2
Asynchronous federated learning aims to solve the straggler problem in heterogeneous environments, i.e., clients have small computational capacities that could cause aggregation de…
Approximate Wireless Communication for Federated Learning
Xiang Ma, Haijian Sun, Rose Qingyang Hu +1
This paper presents an approximate wireless communication scheme for federated learning (FL) model aggregation in the uplink transmission. We consider a realistic channel that reve…
Cognitive Semantic Communication Systems Driven by Knowledge Graph: Principle, Implementation, and Performance Evaluation
Fuhui Zhou, Yihao Li, Ming Xu +4
Semantic communication is envisioned as a promising technique to break through the Shannon limit. However, semantic inference and semantic error correction have not been well studi…
Pricing for Reconfigurable Intelligent Surface Aided Wireless Networks: Models and Principles
Yulan Gao, Yue Xiao, Xianfu Lei +5
Owing to the recent advancements of meta-materials and meta-surfaces, the concept of reconfigurable intelligent surface (RIS) has been embraced to meet the spectral- and energy-eff…
One-to-Many Semantic Communication Systems: Design, Implementation, Performance Evaluation
Han Hu, Xingwu Zhu, Fuhui Zhou +3
Semantic communication in the 6G era has been deemed a promising communication paradigm to break through the bottleneck of traditional communications. However, its applications for…
A New Implementation of Federated Learning for Privacy and Security Enhancement
Xiang Ma, Haijian Sun, Rose Qingyang Hu +1
Motivated by the ever-increasing concerns on personal data privacy and the rapidly growing data volume at local clients, federated learning (FL) has emerged as a new machine learni…
Cognitive Semantic Communication Systems Driven by Knowledge Graph
Fuhui Zhou, Yihao Li, Xinyuan Zhang +3
Semantic communication is envisioned as a promising technique to break through the Shannon limit. However, the existing semantic communication frameworks do not involve inference a…
Intelligent Resource Allocations for IRS-Assisted OFDM Communications: A Hybrid MDQN-DDPG Approach
Wei Wu, Fengchun Yang, Fuhui Zhou +3
In this paper, we study the resource allocation problem for an intelligent reflecting surface (IRS)-assisted OFDM system. The system sum rate maximization framework is formulated b…
Energy Efficiency and Delay Tradeoff in an MEC-Enabled Mobile IoT Network
Han Hu, Weiwei Song, Qun Wang +2
Mobile Edge Computing (MEC) has recently emerged as a promising technology in the 5G era. It is deemed an effective paradigm to support computation-intensive and delay critical app…
An Efficient Deep CNN Design for EH Short-Packet Communications in Multihop Cognitive IoT Networks
Toan-Van Nguyen, Thien Huynh-The, Van-Dinh Nguyen +3
In this paper, we design an efficient deep convolutional neural network (CNN) to improve and predict the performance of energy harvesting (EH) short-packet communications in multi-…
Unmanned Aerial Vehicle Swarm-Enabled Edge Computing: Potentials, Promising Technologies, and Challenges
Wei Wu, Fuhui Zhou, Baoyun Wang +3
Unmanned aerial vehicle (UAV) swarm enabled edge computing is envisioned to be promising in the sixth generation wireless communication networks due to their wide application senso…
When Machine Learning Meets Spectrum Sharing Security: Methodologies and Challenges
Qun Wang, Haijian Sun, Rose Qingyang Hu +1
The exponential growth of internet connected systems has generated numerous challenges, such as spectrum shortage issues, which require efficient spectrum sharing (SS) solutions. C…
Energy-Efficient Design for IRS-Assisted MEC Networks with NOMA
Qun Wang, Fuhui Zhou, Han Hu +1
Energy-efficient design is of crucial importance in wireless internet of things (IoT) networks. In order to serve massive users while achieving an energy-efficient operation, an in…
User Scheduling for Federated Learning Through Over-the-Air Computation
Xiang Ma, Haijian Sun, Qun Wang +1
A new machine learning (ML) technique termed as federated learning (FL) aims to preserve data at the edge devices and to only exchange ML model parameters in the learning process.…
A Novel Automatic Modulation Classification Scheme Based on Multi-Scale Networks
Hao Zhang, Fuhui Zhou, Qihui Wu +2
Automatic modulation classification enables intelligent communications and it is of crucial importance in today's and future wireless communication networks. Although many automati…
Mobility-Aware Offloading and Resource Allocation in MEC-Enabled IoT Networks
Han Hu, Weiwei Song, Qun Wang +2
Mobile edge computing (MEC)-enabled Internet of Things (IoT) networks have been deemed a promising paradigm to support massive energy-constrained and computation-limited IoT device…
Secure and Energy-Efficient Offloading and Resource Allocation in a NOMA-Based MEC Network
Qun Wang, Han Hu, Haijian Sun +1
Energy efficiency and security are two critical issues for mobile edge computing (MEC) networks. With stochastic task arrivals, time-varying dynamic environment, and passive existi…
Energy Efficient Robust Beamforming and Cooperative Jamming Design for IRS-Assisted MISO Networks
Qun Wang, Fuhui Zhou, Rose Qingyang Hu +1
Energy-efficient design and secure communications are of crucial importance in wireless communication networks. However, the energy efficiency achieved by using physical layer secu…
Multi-Agent Deep Reinforcement Learning enabled Computation Resource Allocation in a Vehicular Cloud Network
Shilin Xu, Caili Guo, Rose Qingyang Hu +1
In this paper, we investigate the computational resource allocation problem in a distributed Ad-Hoc vehicular network with no centralized infrastructure support. To support the eve…
Scheduling Policy and Power Allocation for Federated Learning in NOMA Based MEC
Xiang Ma, Haijian Sun, Rose Qingyang Hu
Federated learning (FL) is a highly pursued machine learning technique that can train a model centrally while keeping data distributed. Distributed computation makes FL attractive…
User Preference Learning-Aided Collaborative Edge Caching for Small Cell Networks
Md Ferdous Pervej, Le Thanh Tan, Rose Qingyang Hu
While next-generation wireless communication networks intend leveraging edge caching for enhanced spectral efficiency, quality of service, end-to-end latency, content sharing cost,…
Artificial Intelligence Assisted Collaborative Edge Caching in Small Cell Networks
Md Ferdous Pervej, Le Thanh Tan, Rose Qingyang Hu
Edge caching is a new paradigm that has been exploited over the past several years to reduce the load for the core network and to enhance the content delivery performance. Many exi…