Publications (117)
Fatigue-aware Bandits for Dependent Click Models
Junyu Cao, Wei Sun, Zuo-Jun +2
As recommender systems send a massive amount of content to keep users engaged, users may experience fatigue which is contributed by 1) an overexposure to irrelevant content, 2) bor…
Contention Intensity based Distributed Coordination for V2V Safety Message Broadcast
Jie Gao, Mushu Li, Lian Zhao +2
In this paper, we propose a contention intensity based distributed coordination (CIDC) scheme for safety message broadcast. By exploiting the high-frequency and periodical features…
Collaborative Deep Reinforcement Learning for Resource Optimization in Non-Terrestrial Networks
Yang Cao, Shao-Yu Lien, Ying-Chang Liang +3
Non-terrestrial networks (NTNs) with low-earth orbit (LEO) satellites have been regarded as promising remedies to support global ubiquitous wireless services. Due to the rapid mobi…
Semantic Communications for Wireless Sensing: RIS-aided Encoding and Self-supervised Decoding
Hongyang Du, Jiacheng Wang, Dusit Niyato +5
Semantic communications can reduce the resource consumption by transmitting task-related semantic information extracted from source messages. However, when the source messages are…
Accuracy-Guaranteed Collaborative DNN Inference in Industrial IoT via Deep Reinforcement Learning
Wen Wu, Peng Yang, Weiting Zhang +3
Collaboration among industrial Internet of Things (IoT) devices and edge networks is essential to support computation-intensive deep neural network (DNN) inference services which r…
Enhancing Physical Layer Communication Security through Generative AI with Mixture of Experts
Changyuan Zhao, Hongyang Du, Dusit Niyato +6
AI technologies have become more widely adopted in wireless communications. As an emerging type of AI technologies, the generative artificial intelligence (GAI) gains lots of atten…
Fast mmwave Beam Alignment via Correlated Bandit Learning
Wen Wu, Nan Cheng, Ning Zhang +4
Beam alignment (BA) is to ensure the transmitter and receiver beams are accurately aligned to establish a reliable communication link in millimeter-wave (mmwave) systems. Existing…
Model-Driven Deep Learning for Non-Coherent Massive Machine-Type Communications
Zhe Ma, Wen Wu, Feifei Gao +2
In this paper, we investigate the joint device activity and data detection in massive machine-type communications (mMTC) with a one-phase non-coherent scheme, where data bits are e…
Network Utility Maximization based on Incentive Mechanism for Truthful Reporting of Local Information
Jie Gao, Lian Zhao, Xuemin +1
Classic network utility maximization problems are usually solved assuming all information is available, implying that information not locally available is always truthfully reporte…
Optimal Reliability in Energy Harvesting Industrial Wireless Sensor Networks
Lei Lei, Yiru Kuang, Xuemin +4
For Industrial Wireless Sensor Networks, it is essential to reliably sense and deliver the environmental data on time to avoid system malfunction. While energy harvesting is a prom…
Responsive Regulation of Dynamic UAV Communication Networks Based on Deep Reinforcement Learning
Ran Zhang, Duc Minh, Nguyen +4
In this chapter, the regulation of Unmanned Aerial Vehicle (UAV) communication network is investigated in the presence of dynamic changes in the UAV lineup and user distribution. W…
Energy-Aware Traffic Offloading for Green Heterogeneous Networks
Shan Zhang, Ning Zhang, Sheng Zhou +4
With small cell base stations (SBSs) densely deployed in addition to conventional macro base stations (MBSs), the heterogeneous cellular network (HCN) architecture can effectively…
Digital Twin-Assisted Adaptive Preloading for Short Video Streaming
Shengbo Liu, Wen Wu, Shaofeng Li +3
We propose a digital twin-assisted adaptive preloading scheme to enhance bandwidth efficiency and user quality of experience (QoE) in short video streaming. We first analyze the re…
Edge General Intelligence Through World Models and Agentic AI: Fundamentals, Solutions, and Challenges
Changyuan Zhao, Guangyuan Liu, Ruichen Zhang +11
Edge General Intelligence (EGI) represents a transformative evolution of edge computing, where distributed agents possess the capability to perceive, reason, and act autonomously a…
Split Learning over Wireless Networks: Parallel Design and Resource Management
Wen Wu, Mushu Li, Kaige Qu +6
Split learning (SL) is a collaborative learning framework, which can train an artificial intelligence (AI) model between a device and an edge server by splitting the AI model into…
Self-Sustaining Caching Stations: Towards Cost-Effective 5G-Enabled Vehicular Networks
Shan Zhang, Ning Zhang, Xiaojie Fang +3
In this article, we investigate the cost-effective 5G-enabled vehicular networks to support emerging vehicular applications, such as autonomous driving, in-car infotainment and loc…
Cooperative Edge Caching in User-Centric Clustered Mobile Networks
Shan Zhang, Peter He, Katsuya Suto +4
With files proactively stored at base stations (BSs), mobile edge caching enables direct content delivery without remote file fetching, which can reduce the end-to-end delay while…
An SDN-Based Transmission Protocol with In-Path Packet Caching and Retransmission
Jiayin Chen, Si Yan, Qiang Ye +7
In this paper, a comprehensive software-defined networking (SDN) based transmission protocol (SDTP) is presented for fifth generation (5G) communication networks, where an SDN cont…
Air-Ground Integrated Mobile Edge Networks: Architecture, Challenges and Opportunities
Nan Cheng, Wenchao Xu, Weisen Shi +5
The ever-increasing mobile data demands have posed significant challenges in the current radio access networks, while the emerging computation-heavy Internet of things (IoT) applic…
A Channel-Triggered Backdoor Attack on Wireless Semantic Image Reconstruction
Jialin Wan, Jinglong Shen, Nan Cheng +5
This paper investigates backdoor attacks in image-oriented semantic communications. The threat of backdoor attacks on symbol reconstruction in semantic communication (SemCom) syste…
Digital Twin-Driven Computing Resource Management for Vehicular Networks
Mushu Li, Jie Gao, Conghao Zhou +3
This paper presents a novel approach for computing resource management of edge servers in vehicular networks based on digital twins and artificial intelligence (AI). Specifically,…
Multi-Timescale Control and Communications with Deep Reinforcement Learning -- Part II: Control-Aware Radio Resource Allocation
Lei Lei, Tong Liu, Kan Zheng +2
In Part I of this two-part paper (Multi-Timescale Control and Communications with Deep Reinforcement Learning -- Part I: Communication-Aware Vehicle Control), we decomposed the mul…
Multi-Agent Reinforcement Learning in Wireless Distributed Networks for 6G
Jiayi Zhang, Ziheng Liu, Yiyang Zhu +9
The introduction of intelligent interconnectivity between the physical and human worlds has attracted great attention for future sixth-generation (6G) networks, emphasizing massive…
A Unified Framework for Guiding Generative AI with Wireless Perception in Resource Constrained Mobile Edge Networks
Jiacheng Wang, Hongyang Du, Dusit Niyato +6
With the significant advancements in artificial intelligence (AI) technologies and powerful computational capabilities, generative AI (GAI) has become a pivotal digital content gen…
Artificial Intelligence for Web 3.0: A Comprehensive Survey
Meng Shen, Zhehui Tan, Dusit Niyato +7
Web 3.0 is the new generation of the Internet that is reconstructed with distributed technology, which focuses on data ownership and value expression. Also, it operates under the p…
Towards Edge-assisted Internet of Things: From Security and Efficiency Perspectives
Jianbing Ni, Xiaodong Lin, Xuemin +1
As we are moving towards the Internet of Things (IoT) era, the number of connected physical devices is increasing at a rapid pace. Mobile edge computing is emerging to handle the s…
Catalyzing Cloud-Fog Interoperation in 5G Wireless Networks: An SDN Approach
Peng Yang, Ning Zhang, Yuanguo Bi +3
The piling up storage and compute stacks in cloud data center are expected to accommodate the majority of internet traffic in the future. However, as the number of mobile devices s…
Bi-Directional Mission Offloading for Agile Space-Air-Ground Integrated Networks
Sheng Zhou, Guangchao Wang, Shan Zhang +3
Space-air-ground integrated networks (SAGIN) provide great strengths in extending the capability of ground wireless networks. On the other hand, with rich spectrum and computing re…
Edge-Assisted Accelerated Cooperative Sensing for CAVs: Task Placement and Resource Allocation
Yuxuan Wang, Kaige Qu, Wen Wu +2
In this paper, we propose a novel road side unit (RSU)-assisted cooperative sensing scheme for connected autonomous vehicles (CAVs), with the objective to reduce completion time of…
Low-Latency and Fresh Content Provision in Information-Centric Vehicular Networks
Shan Zhang, Junjie Li, Hongbin Luo +4
In this paper, the content service provision of information-centric vehicular networks (ICVNs) is investigated from the aspect of mobile edge caching, considering the dynamic drivi…
Learning Value of Information towards Joint Communication and Control in 6G V2X
Lei Lei, Kan Zheng, Xuemin +1
As Cellular Vehicle-to-Everything (C-V2X) evolves towards future sixth-generation (6G) networks, Connected Autonomous Vehicles (CAVs) are emerging to become a key application. Leve…
Reliable Distributed Computing for Metaverse: A Hierarchical Game-Theoretic Approach
Yuna Jiang, Jiawen Kang, Dusit Niyato +5
The metaverse is regarded as a new wave of technological transformation that provides a virtual space for people to interact through digital avatars. To achieve immersive user expe…
MAC for Machine Type Communications in Industrial IoT -- Part I: Protocol Design and Analysis
Jie Gao, Weihua Zhuang, Mushu Li +3
In this two-part paper, we propose a novel medium access control (MAC) protocol for machine-type communications in the industrial internet of things. The considered use case featur…
Graph Neural Network Meets Multi-Agent Reinforcement Learning: Fundamentals, Applications, and Future Directions
Ziheng Liu, Jiayi Zhang, Enyu Shi +5
Multi-agent reinforcement learning (MARL) has become a fundamental component of next-generation wireless communication systems. Theoretically, although MARL has the advantages of l…
ProSecutor: Protecting Mobile AIGC Services on Two-Layer Blockchain via Reputation and Contract Theoretic Approaches
Yinqiu Liu, Hongyang Du, Dusit Niyato +5
Mobile AI-Generated Content (AIGC) has achieved great attention in unleashing the power of generative AI and scaling the AIGC services. By employing numerous Mobile AIGC Service Pr…
Collaborative Computing in Non-Terrestrial Networks: A Multi-Time-Scale Deep Reinforcement Learning Approach
Yang Cao, Shao-Yu Lien, Ying-Chang Liang +3
Constructing earth-fixed cells with low-earth orbit (LEO) satellites in non-terrestrial networks (NTNs) has been the most promising paradigm to enable global coverage. The limited…
Can Knowledge Improve Security? A Coding-Enhanced Jamming Approach for Semantic Communication
Weixuan Chen, Qianqian Yang, Shuo Shao +4
As semantic communication (SemCom) attracts growing attention as a novel communication paradigm, ensuring the security of transmitted semantic information over open wireless channe…
Guiding AI-Generated Digital Content with Wireless Perception
Jiacheng Wang, Hongyang Du, Dusit Niyato +5
Recent advances in artificial intelligence (AI), coupled with a surge in training data, have led to the widespread use of AI for digital content generation, with ChatGPT serving as…
Edge Graph Intelligence: Reciprocally Empowering Edge Networks with Graph Intelligence
Liekang Zeng, Shengyuan Ye, Xu Chen +6
Recent years have witnessed a thriving growth of computing facilities connected at the network edge, cultivating edge networks as a fundamental infrastructure for supporting miscel…
Big Data Driven Vehicular Networks
Nan Cheng, Feng Lyu, Jiayin Chen +5
Vehicular communications networks (VANETs) enable information exchange among vehicles, other end devices and public networks, which plays a key role in road safety/infotainment, in…
On the Road to 6G: Visions, Requirements, Key Technologies and Testbeds
Cheng-Xiang Wang, Xiaohu You, Xiqi Gao +16
Fifth generation (5G) mobile communication systems have entered the stage of commercial development, providing users with new services and improved user experiences as well as offe…
Optimal Scheduling in IoT-Driven Smart Isolated Microgrids Based on Deep Reinforcement Learning
Jiaju Qi, Lei Lei, Kan Zheng +3
In this paper, we investigate the scheduling issue of diesel generators (DGs) in an Internet of Things (IoT)-Driven isolated microgrid (MG) by deep reinforcement learning (DRL). Th…
Energy Harvesting-Aided Spectrum Sensing and Data Transmission in Heterogeneous Cognitive Radio Sensor Network
Deyu Zhang, Zhigang Chen Ju Ren, Ning Zhang +4
The incorporation of Cognitive Radio (CR) and Energy Harvesting (EH) capabilities in wireless sensor networks enables spectrum and energy efficient heterogeneous cognitive radio se…
Multi-Timescale Control and Communications with Deep Reinforcement Learning -- Part I: Communication-Aware Vehicle Control
Tong Liu, Lei Lei, Kan Zheng +2
An intelligent decision-making system enabled by Vehicle-to-Everything (V2X) communications is essential to achieve safe and efficient autonomous driving (AD), where two types of d…
A Lyapunov-Guided Diffusion-Based Reinforcement Learning Approach for UAV-Assisted Vehicular Networks with Delayed CSI Feedback
Zhang Liu, Lianfen Huang, Zhibin Gao +4
Low altitude uncrewed aerial vehicles (UAVs) are expected to facilitate the development of aerial-ground integrated intelligent transportation systems and unlocking the potential o…
Energy-Efficient UAV-Assisted Mobile Edge Computing: Resource Allocation and Trajectory Optimization
Mushu Li, Nan Cheng, Jie Gao +4
In this paper, we study unmanned aerial vehicle (UAV) assisted mobile edge computing (MEC) with the objective to optimize computation offloading with minimum UAV energy consumption…
Blockchain-Empowered Lifecycle Management for AI-Generated Content (AIGC) Products in Edge Networks
Yinqiu Liu, Hongyang Du, Dusit Niyato +6
The rapid development of Artificial IntelligenceGenerated Content (AIGC) has brought daunting challenges regarding service latency, security, and trustworthiness. Recently, researc…
A Survey on Semantic Communication Networks: Architecture, Security, and Privacy
Shaolong Guo, Yuntao Wang, Ning Zhang +5
With the rapid advancement and deployment of intelligent agents and artificial general intelligence (AGI), a fundamental challenge for future networks is enabling efficient communi…
MAC for Machine Type Communications in Industrial IoT -- Part II: Scheduling and Numerical Results
Jie Gao, Mushu Li, Weihua Zhuang +3
In the second part of this paper, we develop a centralized packet transmission scheduling scheme to pair with the protocol designed in Part I and complete our medium access control…
Unifying Futures and Spot Market: Overbooking-Enabled Resource Trading in Mobile Edge Networks
Minghui Liwang, Ruitao Chen, Xianbin Wang +2
Securing necessary resources for edge computing processes via effective resource trading becomes a critical technique in supporting computation-intensive mobile applications. Conve…
Semantic-Aware Sensing Information Transmission for Metaverse: A Contest Theoretic Approach
Jiacheng Wang, Hongyang Du, Zengshan Tian +4
With the advancement of network and computer technologies, virtual cyberspace keeps evolving, and Metaverse is the main representative. As an irreplaceable technology that supports…
The Study of Dynamic Caching via State Transition Field -- the Case of Time-Invariant Popularity
Jie Gao, Lian Zhao, Xuemin +1
This two-part paper investigates cache replacement schemes with the objective of developing a general model to unify the analysis of various replacement schemes and illustrate thei…
Communication-Efficient Collaborative LLM Inference over LEO Satellite Networks
Songge Zhang, Wen Wu, Liang Li +3
Low Earth orbit (LEO) satellites play an essential role in intelligent Earth observation by leveraging artificial intelligence models. However, limited onboard memory and excessive…
A Virtual Network Customization Framework for Multicast Services in NFV-enabled Core Networks
Omar Alhussein, Phu Thinh Do, Qiang Ye +7
The paradigm of network function virtualization (NFV) with the support of software defined networking (SDN) emerges as a promising approach for customizing network services in fift…
Cucker-Smale Flocking under Hierarchical Leadership
Jackie, Shen
A mathematical theory on flocking serves the foundation for several ubiquitous multi-agent phenomena in biology, ecology, sensor networks, economy, as well as social behavior like…
Efficient Hybrid Beamforming with Anti-Blockage Design for High-Speed Railway Communications
Meilin Gao, Bo Ai, Yong Niu +5
Future railway is expected to accommodate both train operation services and passenger broadband services. The millimeter wave (mmWave) communication is a promising technology in pr…
Deep Reinforcement Learning for Autonomous Internet of Things: Model, Applications and Challenges
Lei Lei, Yue Tan, Kan Zheng +4
The Internet of Things (IoT) extends the Internet connectivity into billions of IoT devices around the world, where the IoT devices collect and share information to reflect status…
Physical Layer Security Assisted Computation Offloading in Intelligently Connected Vehicle Networks
Yiliang Liu, Wei Wang, Hsiao-Hwa Chen +5
In this paper, we propose a secure computation offloading scheme (SCOS) in intelligently connected vehicle (ICV) networks, aiming to minimize overall latency of computing via offlo…
Software Defined Networking Enabled Wireless Network Virtualization: Challenges and Solutions
Ning Zhang, Peng Yang, Shan Zhang +5
Next generation (5G) wireless networks are expected to support the massive data and accommodate a wide range of services/use cases with distinct requirements in a cost-effective, f…
CSVAR: Enhancing Visual Privacy in Federated Learning via Adaptive Shuffling Against Overfitting
Zhuo Chen, Zhenya Ma, Yan Zhang +8
Although federated learning preserves training data within local privacy domains, the aggregated model parameters may still reveal private characteristics. This vulnerability stems…
Energy and Information Management of Electric Vehicular Network: A Survey
Nan Chen, Miao Wang, Ning Zhang +2
The connected vehicle paradigm empowers vehicles with the capability to communicate with neighboring vehicles and infrastructure, shifting the role of vehicles from a transportatio…
Vehicular Communication Networks in Automated Driving Era
Shan Zhang, Jiayin Chen, Feng Lyu +4
Embedded with advanced sensors, cameras and processors, the emerging automated driving vehicles are capable of sensing the environment and conducting automobile operation, paving t…
Privacy-preserving Intelligent Resource Allocation for Federated Edge Learning in Quantum Internet
Minrui Xu, Dusit Niyato, Zhaohui Yang +5
Federated edge learning (FEL) is a promising paradigm of distributed machine learning that can preserve data privacy while training the global model collaboratively. However, FEL i…
Optimal Stochastic Resource Allocation for Distributed Quantum Computing
Napat Ngoenriang, Minrui Xu, Sucha Supittayapornpong +4
With the advent of interconnected quantum computers, i.e., distributed quantum computing (DQC), multiple quantum computers can now collaborate via quantum networks to perform massi…
Spectral Efficiency Analysis of Uplink-Downlink Decoupled Access in C-V2X Networks
Luofang Jiao, Kai Yu, Yunting Xu +4
The uplink (UL)/downlink (DL) decoupled access has been emerging as a novel access architecture to improve the performance gains in cellular networks. In this paper, we investigate…
Enabling AI-Generated Content (AIGC) Services in Wireless Edge Networks
Hongyang Du, Zonghang Li, Dusit Niyato +5
Artificial Intelligence-Generated Content (AIGC) refers to the use of AI to automate the information creation process while fulfilling the personalized requirements of users. Howev…
Semantic Communications for Artificial Intelligence Generated Content (AIGC) Toward Effective Content Creation
Guangyuan Liu, Hongyang Du, Dusit Niyato +5
Artificial Intelligence Generated Content (AIGC) Services have significant potential in digital content creation. The distinctive abilities of AIGC, such as content generation base…
Networking Architecture and Key Supporting Technologies for Human Digital Twin in Personalized Healthcare: A Comprehensive Survey
Jiayuan Chen, Changyan Yi, Samuel D. Okegbile +3
Digital twin (DT), refers to a promising technique to digitally and accurately represent actual physical entities. One typical advantage of DT is that it can be used to not only vi…
Digital Twin-Based User-Centric Edge Continual Learning in Integrated Sensing and Communication
Shisheng Hu, Jie Gao, Xinyu Huang +5
In this paper, we propose a digital twin (DT)-based user-centric approach for processing sensing data in an integrated sensing and communication (ISAC) system with high accuracy an…
Digital Twin-Empowered Network Planning for Multi-Tier Computing
Conghao Zhou, Jie Gao, Mushu Li +3
In this paper, we design a resource management scheme to support stateful applications, which will be prevalent in 6G networks. Different from stateless applications, stateful appl…
Private, Fair, and Verifiable Aggregate Statistics for Mobile Crowdsensing in Blockchain Era
Miao He, Jianbing Ni, Dongxiao Liu +3
In this paper, we propose FairCrowd, a private, fair, and verifiable framework for aggregate statistics in mobile crowdsensing based on the public blockchain. In specific, mobile u…
SACRM: Social Aware Crowdsourcing with Reputation Management in Mobile Sensing
Ju Ren, Yaoxue Zhang, Kuan Zhang +2
Mobile sensing has become a promising paradigm for mobile users to obtain information by task crowdsourcing. However, due to the social preferences of mobile users, the quality of…
Dynamic Human Digital Twin Deployment at the Edge for Task Execution: A Two-Timescale Accuracy-Aware Online Optimization
Yuye Yang, You Shi, Changyan Yi +5
Human digital twin (HDT) is an emerging paradigm that bridges physical twins (PTs) with powerful virtual twins (VTs) for assisting complex task executions in human-centric services…
An Enhanced Dual-Currency VCG Auction Mechanism for Resource Allocation in IoV: A Value of Information Perspective
Wei Wang, Nan Cheng, Conghao Zhou +5
The Internet of Vehicles (IoV) is undergoing a transformative evolution, enabled by advancements in future 6G network technologies, to support intelligent, highly reliable, and low…
Generative AI for Secure Physical Layer Communications: A Survey
Changyuan Zhao, Hongyang Du, Dusit Niyato +6
Generative Artificial Intelligence (GAI) stands at the forefront of AI innovation, demonstrating rapid advancement and unparalleled proficiency in generating diverse content. Beyon…
Energy-Sustainable Traffic Steering for 5G Mobile Networks
Shan Zhang, Ning Zhang, Sheng Zhou +4
Renewable energy harvesting (EH) technology is expected to be pervasively utilized in the next generation (5G) mobile networks to support sustainable network developments and opera…
Spatial Traffic Shaping in Heterogeneous Cellular Networks with Energy Harvesting
Shan Zhang, Sheng Zhou, Jie Gong +4
Energy harvesting (EH), which explores renewable energy as a supplementary power source, is a promising 5G technology to support the huge energy demand of heterogeneous cellular ne…
The Design of Dynamic Probabilistic Caching with Time-Varying Content Popularity
Jie Gao, Shan Zhang, Lian Zhao +2
In this paper, we design dynamic probabilistic caching for the scenario when the instantaneous content popularity may vary with time while it is possible to predict the average con…
Resource Slicing with Cross-Cell Coordination in Satellite-Terrestrial Integrated Networks
Mingcheng He, Huaqing Wu, Conghao Zhou +2
Satellite-terrestrial integrated networks (STIN) are envisioned as a promising architecture for ubiquitous network connections to support diversified services. In this paper, we pr…
Heterogeneous Ultra-Dense Networks with Traffic Hotspots: A Unified Handover Analysis
He Zhou, Haibo Zhou, Jianguo Li +4
With the ever-growing communication demands and the unceasing miniaturization of mobile devices, the Internet of Things is expanding the amount of mobile terminals to an enormous l…
VoI-Driven Joint Optimization of Control and Communication in Vehicular Digital Twin Network
Lei Lei, Kan Zheng, Jie Mei +2
The vision of sixth-generation (6G) wireless networks paves the way for the seamless integration of digital twins into vehicular networks, giving rise to a Vehicular Digital Twin N…
Dual-Scale Channel Estimation in Sensing-Assisted Communication Systems: Joint Time Allocation and Beamforming Design
Bai Zhiyue, Dai Minghui, Hou Fen +4
In this paper, we propose a novel integrated sensing and communication (ISAC)-enabled dual-scale channel estimation framework, where large-scale channel estimation benefits from se…
Channel-Feedback-Free Transmission for Downlink FD-RAN: A Radio Map based Complex-valued Precoding Network Approach
Jiwei Zhao, Jiacheng Chen, Zeyu Sun +4
As the demand for high-quality services proliferates, an innovative network architecture, the fully-decoupled RAN (FD-RAN), has emerged for more flexible spectrum resource utilizat…
RadioDiff-Inverse: Diffusion Enhanced Bayesian Inverse Estimation for ISAC Radio Map Construction
Xiucheng Wang, Zhongsheng Fang, Nan Cheng +4
Radio maps (RMs) are essential for environment-aware communication and sensing, providing location-specific wireless channel information. Existing RM construction methods often rel…
Energy-Efficient Localization and Tracking of Mobile Devices in Wireless Sensor Networks
Kan Zheng, Hang Li, Lei Lei +4
Wireless sensor networks (WSNs) are effective for locating and tracking people and objects in various industrial environments. Since energy consumption is critical to prolonging th…
AoI-aware Sensing Scheduling and Trajectory Optimization for Multi-UAV-assisted Wireless Backscatter Networks
Yusi Long, Songhan Zhao, Shimin Gong +4
This paper considers multiple unmanned aerial vehicles (UAVs) to assist sensing data transmissions from the ground users (GUs) to a remote base station (BS). Each UAV collects sens…
A Digital Twin-based Intelligent Network Architecture for Underwater Acoustic Sensor Networks
Shanshan Song, Bingwen Huangfu, Jiani Guo +4
Underwater acoustic sensor networks (UASNs) drive toward strong environmental adaptability, intelligence, and multifunctionality. However, due to unique UASN characteristics, such…
DQCO: Distributed Quantum Computing for Collaborative Optimization in Future Networks
Napat Ngoenriang, Minrui Xu, Jiawen Kang +4
With the advantages of high-speed parallel processing, quantum computers can efficiently solve large-scale complex optimization problems in future networks. However, due to the unc…
Cloud-Edge Coordinated Processing: Low-Latency Multicasting Transmission
Shiwen He, Ju Ren, Jiaheng Wang +5
Recently, edge caching and multicasting arise as two promising technologies to support high-data-rate and low-latency delivery in wireless communication networks. In this paper, we…
Beef up mmWave Dense Cellular Networks with D2D-Assisted Cooperative Edge Caching
Wen Wu, Ning Zhang, Nan Cheng +4
Edge caching is emerging as the most promising solution to reduce the content retrieval delay and relieve the huge burden on the backhaul links in the ultra-dense networks by proac…
Joint Scheduling and Power Allocations for Traffic Offloading via Dual-Connectivity
Yuan Wu, Yanfei He, Liping Qian +3
With the rapid growth of mobile traffic demand, a promising approach to relieve cellular network congestion is to offload users' traffic to small-cell networks. In this paper, we i…
Performance Analysis and Enhancement of Beamforming Training in 802.11ad
Wen Wu, Nan Cheng, Ning Zhang +4
Beamforming (BF) training is crucial to establishing reliable millimeter-wave communication connections between stations (STAs) and an access point. In IEEE 802.11ad BF training pr…
RIFL: A Reliable Link Layer Network Protocol for Data Center Communication
Qianfeng, Shen, Jun Zheng +1
More and more latency-sensitive services and applications are being deployed into the data center. Performance can be limited by the high latency of the network interconnect. Becau…
Integration of Mixture of Experts and Multimodal Generative AI in Internet of Vehicles: A Survey
Minrui Xu, Dusit Niyato, Jiawen Kang +6
Generative AI (GAI) can enhance the cognitive, reasoning, and planning capabilities of intelligent modules in the Internet of Vehicles (IoV) by synthesizing augmented datasets, com…
Fast AI Model Partition for Split Learning over Edge Networks
Zuguang Li, Wen Wu, Shaohua Wu +2
Split learning (SL) is a distributed learning paradigm that can enable computation-intensive artificial intelligence (AI) applications by partitioning AI models between mobile devi…
RadioMamba: Breaking the Accuracy-Efficiency Trade-off in Radio Map Construction via a Hybrid Mamba-UNet
Honggang Jia, Nan Cheng, Xiucheng Wang +4
Radio map (RM) has recently attracted much attention since it can provide real-time and accurate spatial channel information for 6G services and applications. However, current deep…
Hybrid Reinforcement Learning-based Sustainable Multi-User Computation Offloading for Mobile Edge-Quantum Computing
Minrui Xu, Dusit Niyato, Jiawen Kang +5
Exploiting quantum computing at the mobile edge holds immense potential for facilitating large-scale network design, processing multimodal data, optimizing resource management, and…
Towards Intelligent Transportation with Pedestrians and Vehicles In-the-Loop: A Surveillance Video-Assisted Federated Digital Twin Framework
Xiaolong Li, Jianhao Wei, Haidong Wang +7
In intelligent transportation systems (ITSs), incorporating pedestrians and vehicles in-the-loop is crucial for developing realistic and safe traffic management solutions. However,…
Personalized QoE Enhancement for Adaptive Video Streaming: A Digital Twin-Assisted Scheme
Xinyu Huang, Conghao Zhou, Wen Wu +4
In this paper, we present a digital twin (DT)-assisted adaptive video streaming scheme to enhance personalized quality-of-experience (PQoE). Since PQoE models are user-specific and…
Cost-Effective Two-Stage Network Slicing for Edge-Cloud Orchestrated Vehicular Networks
Wen Wu, Kaige Qu, Peng Yang +4
In this paper, we study a network slicing problem for edge-cloud orchestrated vehicular networks, in which the edge and cloud servers are orchestrated to process computation tasks…