Yuan Wu

Hong Kong University of Science and Technology | UST

Due to the limitations of computing resources and battery capacity, the computation tasks of ground devices can be offloaded to edge servers for processing. Moreover, with the development of the low earth orbit (LEO) satellite technology, LEO satellite-terrestrial edge computing can realize a global coverage network to provide seamless computing se...

Cooperative perception is a promising paradigm to tackle the perception limitations of a single intelligent vehicle (IV) to enhance the driving safety and efficiency in intelligent vehicular networks. However, the real-time transmission and computation-intensive fusion of raw sensing data raise new challenges for satisfying the stringent delay requ...

Containers have gained popularity in Edge Computing (EC) networks due to their lightweight and flexible deployment advantage. In resource-constrained EC environments, overbooking container resources can substantially improve resource utilization. However, existing work overlooks the complex interplay between resource provisioning and container sche...

With the explosive development of mobile computing, federated learning (FL) has been considered as a promising distributed training framework for addressing the shortage of conventional cloud based centralized training. In FL, local model owners (LMOs) individually train their respective local models and then upload the trained local models to the...

The emerging multi-access edge computing (MEC) technology effectively enhances the wireless streaming performance of 360-degree videos. By connecting a user's head-mounted device (HMD) to a smart MEC platform, the edge server (ES) can efficiently perform adaptive tile-based video streaming to improve the user's viewing experience. Under constrained...

Federated learning (FL) has gained widespread adoption in Internet of Things (IoT) applications, promoting the evolution of IoT towards artificial intelligence of Things (AIoT). However, IoT devices are still vulnerable to various privacy inference attacks in FL. While current solutions aim to protect the privacy of devices during model training, t...

Network slicing has been envisioned to play a crucial role in supporting various vehicular applications with diverse performance requirements in dynamic Vehicle-to-Everything (V2X) communications systems. However, time-varying Service Level Agreements (SLAs) of slices and fast-changing network topologies in V2X scenarios may introduce new challenge...

Dual-function radar-communication (DFRC) can alleviate spectrum congestion and competition with the spectrum-sharing architecture for next-generation wireless networks. In this paper, we consider the problem of robust beamforming in millimeter wave (mmWave) DFRC systems. Unlike most existing works which assume that the angle-of-arrival (AoA)/angle-...

Distributed Artificial Intelligence (AI) model training over mobile edge networks encounters significant challenges due to the data and resource heterogeneity of edge devices. The former hampers the convergence rate of the global model, while the latter diminishes the devices' resource utilization efficiency. In this paper, we propose a generative...

Split federated learning (SFL) has been regarded as an efficient paradigm to enable both federated learning and reduce the computation burdens at the devices by allowing them to train parts of the model. However, deploying SFL over resource-constrained vehicular edge networks is challenging, and a cost-effective scheme is necessitated to minimize t...

An unmanned aerial vehicle (UAV)-enabled intelligent transportation system utilizes a set of UAVs to collect and process surveillance data for transportation management. Subsequently, the processing results of the UAVs are transmitted to a control center that makes a centralized transportation management decision based on the fusion of all processi...

Mobile Edge Computing (MEC) has envisioned to be a promising technology to provide more efficient services for computation-intensive but delay-sensitive onboard mobile services. In this paper, the Non-Orthogonal Multiple Access (NOMA) technology is applied in a vehicular edge computing network, in which vehicular users (VUs) can offload partial com...

Symbiotic radio, which exploits the benefits of passive communications and cognitive radio via backscattering or ambient reflecting, is a promising paradigm to support a large amount of Internet of Things devices with high spectrum efficiency and energy efficiency. For edge intelligence, data collection from heterogeneous devices including wireless...

Artificial intelligence generated content (AIGC) has emerged as a promising technology to improve the efficiency, quality, diversity and flexibility of the content creation process by adopting a variety of generative AI models. Deploying AIGC services in wireless networks has been expected to enhance the user experience. However, the existing AIGC...

The integration of unmanned aerial vehicles (UAVs) and marine communication networks has been emerging as a promising paradigm to cater for the growing maritime activities, e.g., marine environment monitoring and ocean resource exploration. The increasing growth of marine applications and services poses challenges for processing marine data, while...

Integrated sensing and communication (ISAC) provides a spectrum-efficient approach for simultaneously enabling reliable data transmission and high-quality sensing. This paper investigates an ISAC-enabled multi-device cooperative sensing system in which the devices perform cooperative sensing towards multiple targets in a time-division manner. Withi...

Semantic communication (SemComm) has emerged as new paradigm shifts.Most existing SemComm systems transmit continuously distributed signals in analog fashion.However, the analog paradigm is not compatible with current digital communication frameworks. In this paper, we propose an alternating multi-phase training strategy (AMP) to enable the joint t...

In recent years, the Internet of Things (IoT) and mobile communication technologies have developed rapidly. Meanwhile, many delay-sensitive and computation-intensive IoT services have been widely applied. Because of the limited computing resources, storage, and battery capacity of IoT devices, mobile edge computing (MEC) is emerging as a promising...

Integrated sensing and communication (ISAC) and edge intelligence are essential components for the next generation wireless networks. ISAC provides a spectrum-efficient paradigm to collect and transfer sensing data for edge intelligence. Multi-station sensing, as a cooperative sensing scheme to perform the sensing tasks towards a number of targets,...

Mobile edge computing (MEC) enables the caching of various services close to users, thereby reducing service delay for emerging applications. However, realizing efficient and secure computation offloading is challenging due to the limited storage capacity of MEC servers and the offloading security issue arising from the open nature of wireless chan...

Integrated sensing and communication (ISAC) provides a promising paradigm for future beyond 5G (B5G) and 6G networks. As an important application of edge intelligence, image analysis (e.g., recognition) at the edge networks has attracted lots of interests. In this paper, we propose an image analysis oriented ISAC, in which the image captured by a w...

The rapid development of large models such as GPT-4 and Midjourney has spawned worldwide attention in various fields. To practically deploy large model services in downstream tasks, cloud-edge collaboration mechanism offers an appealing solution by seamlessly sharing fresh data, knowledge, and resources between the cloud and distributed edge nodes....

With the development of intelligent transportation systems (ITS), digital twin (DT) technology is becoming increasingly widespread in the application of connected automated vehicles (CAV) to enhance driving safety. However, when DT systems are used for driving safety decisions through virtual control of reality and virtual reflection of reality, de...

Unmanned Aerial Vehicle (UAV)-assisted Low Earth Orbit (LEO) satellite edge computing (ULSE) networks can address the challenge communications issues in areas with harsh terrain and achieve global wireless coverage to provide services for mobile user devices (MUDs). This paper studies the LEO-UAV task offloading problem where MUDs compete for limit...

Efficient federated learning (FL) in mobile edge networks faces challenges due to energy-consuming on-device training and wireless transmission. Optimizing the neural network structures is an effective approach to achieving energy savings. In this paper, we present a Snowball FL training with expanding neural network structure, which starts with a...

The Industrial Internet of Things (IIoT) is a key application of 5th Generation Mobile Communication Technology (5G), with latency-sensitive data transmission forming the foundation of IIoT. In this paper, we study the latency-sensitive data transmission in IIoT with the assistance of relay nodes based on the Non-Orthogonal Multiple Access-Wireless...

The surge in mobile vehicles and data traffic in Vehicular Edge Computing and Networks (VECONs) requires innovative approaches for low latency, stable connectivity, and efficient resource usage in fast-moving vehicles. Existing studies have identified that utilizing digital twins (DTs) can effectively improve service quality in VECONs. However, it...

As an emerging technology, Digital Twin (DT) can provide a virtual representation of transportation infrastructures to achieve efficient and precise management of Intelligent Transportation Systems (ITS). However, a mixed traffic scenario of coexisting intelligent connected vehicles (ICVs) and non-intelligent connected vehicles (N-ICVs) increases c...

Recently, edge content delivery has been promoted for video applications in unmanned aerial vehicle (UAV)-assisted vehicular networks (UVNs). UAVs could proactively cache (video) contents and transmit them to nearby vehicular users, thereby significantly mitigating delivery latency. However, since UAVs are typically deployed by untrusted third part...

Generative artificial intelligence (AI) in edge networks has excelled in delivering human-level creative services close to the end users. However, providing customized intelligence services to a wide range of end clients remains challenging due to the diverse demands of edge applications. In this paper, we present FlexGen, an efficient generative A...

With the increasing exploration of marine resources, various marine wireless devices have been rapidly deployed for different marine applications such as marine navigation, ocean environment monitoring, and seabed resource exploitation. However, due to long transmission delay and low data rate between marine wireless devices and the cloud, it is ch...

To provide a dependency-aware application, multiple UAVs are employed to serve a ground user with a set of interdependent tasks. This leads to a new computing paradigm called as multi-UAV enabled aerial edge computing (MU-AEC). For the large-scale application of MU-AEC, both the task-centric objective and UAV-centric objective should be simultaneou...

Integrated sensing and communication (ISAC) is regarded as an important paradigm in future networks. In this work, we consider that the ISAC device can offload its collected sensing data to multiple edge-servers for remote processing via multi-access mobile edge computing (MEC). To this end, we formulate a joint optimization problem of the beamform...

The explosively increasing development of marine communication networks will improve the quality of service (QoS) of marine applications (e.g., ocean farm and marine tourism), which has attracted much attention from both academia and industrial in recent years. However, real-time data processing for diverse marine tasks (especially those computing-...

Model update compression is a widely used technique to alleviate the communication cost in federated learning (FL). However, there is evidence indicating that the compression-based FL system often suffers the following two issues, i) the implicit learning performance deterioration of the global model due to the inaccurate update, ii) the limitation...

Integrated sensing and communication (ISAC), which enables the joint radar sensing and data communications, shows its great potential in many intelligent applications. In this paper, we investigate the unmanned aerial vehicle (UAV) aided ISAC with mobile edge computing (MEC), where the ISAC device deployed on the UAV senses multiple targets with th...

Integrated sensing and communication (ISAC) system has been expected to play a vital role in future wireless networks and services. In this paper, we investigate a non-orthogonal multiple access (NOMA)-aided ISAC system in which the ISAC base station utilizes NOMA to serve multiple NOMA-users while performing radar sensing towards a group of sensin...

In this paper, we investigate an unmanned aerial vehicle (UAV)-assisted integrated communication and localization network in emergency scenarios where a single UAV is deployed as both an airborne base station (BS) and anchor node to assist ground BSs in communication and localization services. We formulate an optimization problem to maximize the su...

Metaverse enables users to communicate, collaborate and socialize with each other through their digital avatars. Due to the spatio-temporal characteristics, co-located users are served well by performing their software components in a collaborative manner such that a Metaverse service provider (MSP) eliminates redundant data transmission and proces...

Driven by the increasing interests of multi-tier computing architecture, this paper considers a hybrid non-orthogonal multiple access (NOMA) and frequency division multiple access (FDMA) assisted two-tier edge-cloudlet multi-access computation offloading. In particular, part of the computation tasks of the edge-computing user (EU) can be offloaded...

Metaverse enables users to communicate, collaborate and socialize with each other through their digital avatars. Due to the spatio-temporal characteristics, co-located users are served well by performing their software components in a collaborative manner such that a Metaverse service provider (MSP) eliminates redundant data transmission and proces...

Recently, an origin fully-decoupled radio access network (FD-RAN) inspired by neurotransmission has been proposed for B5G/6G mobile communication networks, which achieves the potentials of improving the spectrum efficiency, reducing the energy consumption and meeting personalized user requirement through profound resource cooperation. To explore ne...

Artificial intelligence generated content (AIGC) has emerged as a promising technology to improve the efficiency, quality, diversity and flexibility of the content creation process by adopting a variety of generative AI models. Deploying AIGC services in wireless networks has been expected to enhance the user experience. However, the existing AIGC...

Nowadays, wireless charging has become one of the most popular technologies in Internet of Things (IoT), which makes electric devices battery-free and flexible. The electromagnetic coupling in antenna design is important to push the range limits beyond the near field. Previous studies did not consider the coupling among coils and they do not work f...

As a promising framework for distributed machine learning (ML), wireless federated learning (FL) faces the threat of eavesdropping attacks when a trained ML model is sent over a radio channel. To address this threat, we propose channel sharing-based artificial jamming to increase the secrecy throughput of FL clients (FCs). Specifically, when an FC...

Spectrum sensing can effectively improve the spectrum utilization. In practice, it is difficult to sense whether the spectrum is occupied or not due to the low signal energy at very low signal-to-noise ratio (SNR) (e.g., -20dB). To overcome this issue, this letter considers the correlation of the time-frequency domains, and proposes a ConvLSTM base...

The explosive development of the Internet of Things (IoT) has led to increased interest in mobile edge computing (MEC), which provides computational resources at network edges to accommodate computation-intensive and latency-sensitive applications. Intelligent reflecting surfaces (IRSs) have gained attention as a solution to overcome blockage probl...

Wireless federated learning (FL) is envisioned as a promising paradigm of distributed learning in wireless networks without disclosing users' data privacy. However, radio channel leads to a potential risk of eavesdropping attack when sending the trained model data in wireless networks. To address this eavesdropping attack, in this work, we propose...

In this work, we investigate the challenging problem of on-demand semantic communication over heterogeneous wireless networks. We propose a fidelity-adjustable semantic transmission framework (FAST) that empowers wireless devices to send data efficiently under different application scenarios and resource conditions. To this end, we first design a d...

The increasing growth of maritime activities leads to the challenges for processing the maritime data. However, the resources-limited maritime devices cannot meet the requirements of transmission delay and energy consumption. In this paper, we investigate the resource allocation for computation offloading in maritime communication networks via game...

In this work, we investigate the challenging problem of on-demand federated learning (FL) over heterogeneous edge devices with diverse resource constraints. We propose a cost-adjustable FL framework, named AnycostFL, that enables diverse edge devices to efficiently perform local updates under a wide range of efficiency constraints. To this end, we...

Integrated terrestrial and non-terrestrial networks (TNTNs) have become promising architecture for enabling ubiquitous connectivity. Smart remote sensing is one of the typical applications of TNTNs that collects and analyzes various dimensions of remote sensing data by deploying Internet of Things (IoT) sensors and edge computing in terrestrial, sp...

Virtual reality (VR) provides users with an immersive and interactive experience through head-mounted devices, which has attracted increasing attention in recent years. Specifically, tile-based VR content transmission provides a promising approach to alleviate the conflict between limited bandwidth and high-performance requirements (e.g., high-reso...

Digital twin has been emerging as a promising paradigm that connects physical entities and digital space, and continuously evolves to optimize the physical systems. In this paper, we focus on studying efficient communication and computation scheme when constructing the Marine Internet of Things (M-IoT)’s digital twin with secrecy provisioning. Spec...

Federated learning (FL) is an emerging distributed learning paradigm widely used in vehicular networks, where vehicles are enabled to train the deep model for the server while keeping private data locally. However, the annotation of private data by vehicular users is very difficult since the high costs and professional needs, and one solution is th...

Federated Learning (FL) enables the distributed machine learning (ML) without violating the privacy of local users. In the scenario wireless FL, it is challenging for some local clients to establish reliable connections with the parameter server due to the potential long-distance transmission. To address this issue, unmanned aerial vehicle (UAV) ca...

This article explores the optimal offloading strategy in the Internet of Vehicles (IoVs), which is challenged by three issues. First, the resources of edge servers are shared by multiple vehicles, leading to random changes over time. Second, as a vehicle would drive across consecutive edge servers, the offloading strategy needs to consider the over...

The rapid development of immersive technologies is propelling the emergence of extended reality (XR), a promising use case that submerges users into a virtual universe. To enable XR, devices equipped with a large number of sensors are necessary, and the diverse types and functions of sensors lead to different sensing and communication paradigms in...

As a key paradigm of future 6G networks, Space-Air-Ground Integrated Networks (SAGIN) has been envisioned to provide numerous intelligent applications that necessitate the cooperation of a multitude of terrestrial devices for machine learning (ML) model training. Utilizing the satellite as the central server, federated learning (FL) offers a promis...

Integrated sensing and communication (ISAC) is a promising paradigm for supporting emerging wireless services and applications that require both high-throughput data transmission and accurate environment sensing. In this paper, we investigate the energy-efficient channel sharing aided ISAC with sensing scheduling, in which the ISAC base station (BS...

The orthogonal frequency-division multiplexing (OFDM) is widely used in modern radio communications because of its efficient spectrum utilization. As we know, the adaptive modulation can efficiently improve the spectrum utilization of OFDM systems, in comparison with the non-adaptive modulation. For this, we design a learning-driven automatic modul...

The explosive development of the Internet of Things (IoT) has led to increased interest in mobile edge computing (MEC), which provides computational resources at network edges to accommodate computation-intensive and latency-sensitive applications. Intelligent reflecting surfaces (IRSs) have gained attention as a solution to overcome blockage probl...

Non-orthogonal multiple access (NOMA) and energy-harvesting (EH) relay have been envisioned as promising technologies in Narrowband Internet of Things (NB-IoT) networks to efficiently improve the spectral-energy efficiency of networks and the massive connectivity of devices. However, the successive interference cancellation (SIC) ordering of NOMA h...

Due to the massive computing demands of the Internet of Things, mobile edge computing (MEC) has been extensively investigated as a means of providing computation-intensive and latency-sensitive services at the network edge. With increasing density of base stations (BSs), users are simultaneously served by multiple BSs, leading to the multicell MEC...

To provide a better support for various vehicular applications, digital twin (DT), as an emerging technology, can enable a virtual presentation of physical vehicular networks to reflect the current network state through real-time data updating. However, the constrained resources and high data updating cost may degrade the performance of DT. In this...

Integrated sensing and communication (ISAC) provides an emerging paradigm for enabling a variety of next-generation wireless services and applications. Due to the limited computation resources on ISAC devices and the latency as well as the reliability requirements, we propose a paradigm of mobile edge computing (MEC) aided ISAC with short-packet tr...

Proof of work (PoW), as the representative consensus protocol for blockchain, consumes enormous amounts of computation and energy to determine bookkeeping rights among miners but does not achieve any practical purposes. To address the drawback of PoW, we propose a novel energy-recycling consensus mechanism named platform-free proof of federated lea...

The smart ocean has been regarded as an integrated sensing, communication, and computing ecosystem developed for connecting marine objects in surface and underwater environments. The development of the smart ocean is expected to support a variety of marine applications and services such as resource exploration, marine disaster rescuing, and environ...

In this letter, we propose an integrated sensing and communication (ISAC) assisted energy-efficient mobile edge computing (MEC). To address the performance degradation due to interference between the radar sensing and MEC, we leverage advanced intelligent reflecting surface (IRS) to improve both the performance of the radar sensing and MEC. We adop...