Zehui Xiong

• Doctor of Philosophy
• Professor (Assistant) at Singapore University of Technology and Design

In recent years, unmanned aerial vehicle (UAV) swarm networks have been widely utilized across various fields. Moreover, the advent of 6G technologies has rapidly expanded the size of UAV swarm networks, making efficient routing a critical challenge. Nevertheless, most routing methods in UAV swarm networks are IP-based. As the network scales, the m...

Exploiting quantum computing at the mobile edge holds immense potential for facilitating large-scale network design, processing multimodal data, optimizing resource management, and enhancing network security. In this paper, we propose a pioneering paradigm of mobile edge quantum computing (MEQC) that integrates quantum computing capabilities into c...

The Internet of Things (IoT) collects large volumes of diverse data, with graph data as a critical component, and extensively utilizes Federated Graph Learning (FGL) to process this data while preserving data security. However, the graph data collected by different IoT institutions are relatively independent due to various factors (e.g., data colle...

Generative AI (GenAI) is driving the intelligence of wireless communications. Due to data limitations, random generation, and dynamic environments, GenAI may generate channel information or optimization strategies that violate physical laws or deviate from actual real-world requirements. We refer to this phenomenon as wireless hallucination, which...

The explosive growth of the Internet of Things (IoT) has dramatically increased the demand for secure mechanisms to protect against unauthorized access and attacks. Traditionally, expensive Software-Defined Radios (SDRs) have been utilized to gather IoT physical features, which are critical for reliable authentication. However, the high cost of SDR...

The increasing complexity and scale of modern telecommunications networks demand intelligent automation to enhance efficiency, adaptability, and resilience. Agentic AI has emerged as a key paradigm for intelligent communications and networking, enabling AI-driven agents to perceive, reason, decide, and act within dynamic networking environments. Ho...

The rapid proliferation of Internet of Things (IoT) devices and the deployment of edge computing infrastructures have significantly advanced data processing and network communications. Federated Learning (FL), leveraging these developments , offers a decentralized approach to learning across edge devices while preserving local privacy. However, tra...

Driven by the rapid proliferation of Internet of Things (IoT) devices and the evolution of mobile networks, the global network landscape is undergoing a transformative shift that necessitates advanced network management techniques to handle complex data and various service demands. In this context , Generative Artificial Intelligence (GAI) emerges...

Mobile edge Large Language Model (LLM) deployments face inherent constraints, such as limited computational resources and network bandwidth. Although Retrieval-Augmented Generation (RAG) mitigates some challenges by integrating external knowledge bases, inefficient cache management can still result in high retrieval latency and frequent cache updat...

In recent years, Named Data Networking (NDN) has garnered widespread attention in academia as a novel network architecture capable of addressing issues such as the vulnerability of end-to-end connections in IP-based networks. In NDN, nodes employ a pull-push architecture, communicate with each other by exchanging Interest packets and Data packets....

Wireless sensing systems have been employed in the field of healthcare, environment monitoring, and smart agriculture, etc. Since the freshness and accuracy indicators of the sensing data are critical to wireless sensing systems, it is of great significance to ensure their performances simultaneously, i.e., the Age of Information (AoI) and informat...

The low-altitude economy provides new opportunities for target search, as unmanned aerial vehicles (UAVs) improve search efficiency through aerial surveillance and data collection. UAVs support overhead views of the search area, while ground vehicles (GVs) offer side views, facilitating effective collaboration in wireless networks. However, the lim...

AI technologies have become increasingly adopted in wireless communications. As an emerging type of AI technologies, generative artificial intelligence (GAI) is gaining attention in communication security. Due to its powerful learning ability, GAI models have demonstrated superiority over conventional AI methods. However, GAI still has several limi...

The rapid development of generative artificial intelligence (AI) technologies, including large language models (LLMs), has brought transformative changes to various fields. However, deploying such advanced models on mobile and edge devices remains challenging due to their high computational, memory, communication, and energy requirements. To addres...

With the rapid advancement of technology, intelligent applications increasingly require higher computing power, driving the evolution of the end-edge-cloud Collaborative Scheduling (CS) paradigm. However, this paradigm primarily focuses on vertical collaboration, neglecting horizontal coordination among ubiquitous heterogeneous computing resources,...

The joint optimization of rate-splitting multiple access (RSMA) and reconfigurable intelligent surface (RIS) offers a mutually beneficial solution. In this paper, we study a RIS-assisted downlink user grouping-based hierarchical RSMA communication network, where the base station transmits the common streams and private streams simultaneously to ser...

Generative artificial intelligence (GenAI) technologies represent an important advancement in the field of AI, particularly for their capabilities in text and image generation. Over-the-air wireless federated learning (OA-WFL) can utilize the wireless waveform superposition property to achieve efficient model aggregation, thereby providing support...

Enhanced by onboard computing resources and inter-satellite links (ISLs), large-scale satellite networks (SNs) can supplement terrestrial networks, facilitating real-time edge computing and transmission in remote areas at low latency. This capability benefits applications such as real-time remote object tracking, vehicular edge computing, and envir...

The utilization of emergent generative artificial intelligence (GAI) within the realm of unmanned vehicles (UVs) can boost edge intelligence and potentially enhance the efficiency and effectiveness of rescue operations. However, to facilitate specialized generative edge intelligence in dynamic UV networks, GAI models need to tap into local data and...

Vehicle-to-everything (V2X) communication supports numerous tasks, from driving safety to entertainment services. To achieve a holistic view, vehicles are typically equipped with multiple sensors. However, processing large volumes of multimodal data increases transmission load, while the dynamic nature of vehicular networks adds to transmission ins...

The Internet of everything, a potential direction for the next-generation Internet, positions edge collaboration as a promising computing paradigm to address the workload dispersion and resource constraints inherent in traditional edge computing frameworks. However, the increasing complexity of cross-domain networks introduces challenges for effici...

With the increasing emphasis on data privacy, federated learning (FL) networks show great potential through distributed training without directly sharing the raw data. However, the coverage of FL terrestrial servers is usually limited. Therefore, we propose leveraging the unmanned aerial vehicle (UAV) as a mobile flying server to further improve th...

Generative diffusion models like Stable Diffusion are at the forefront of the thriving field of generative models today, celebrated for their robust training methodologies and high-quality photorealistic generation capabilities. These models excel in producing rich content, establishing them as essential tools in the industry. Building on this foun...

Web 3.0 pursues the establishment of decentralized ecosystems based on blockchain technologies to drive the digital transformation of physical commerce and governance. Through consensus algorithms and smart contracts in blockchain, which are based on cryptography technologies, digital identity, digital asset management, decentralized autonomous org...

The rapid development of next-generation networking technologies underscores their transformative role in revolutionizing modern communication systems, enabling faster, more reliable, and highly interconnected solutions. However, such development has also brought challenges to network optimizations. Thanks to the emergence of Large Language Models...

Large Language Models (LLMs) have significantly advanced communications fields, such as Telecom Q\&A, mathematical modeling, and coding. However, LLMs encounter an inherent issue known as hallucination, i.e., generating fact-conflicting or irrelevant content. This problem critically undermines the applicability of LLMs in communication systems yet...

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 Providers (MASPs), ubiquitous and low-latency AIGC services for clients can be realized. Nonetheless, the interactions between clients and MASPs in public mobile networks,...

By utilizing intelligent mobile terminals, mobile crowdsensing (MCS) can realize the sensing data collection effectively and economically. However, the privacy security and freshness quality of the obtained sensing data are two major concerns to be addressed in MCS, as they directly impact the system security and timeliness performance. In this reg...

Recently, generative AI has attracted much attention from both academic and industrial fields, due to its potential especially in data generation and synthesis aspects. Simultaneously, secure and privacy-preserving mobile crowdsensing (SPPMCS) has been widely applied in data collection/acquisition due to advantages of low deployment cost, flexible...

In mobile edge computing (MEC) systems, multiple unmanned aerial vehicles (UAVs) can be utilized as aerial servers to provide computing, communication, and storage services for edge users, called UAV-assisted MEC, which has emerged as a promising technology to improve both the computing and communication performances. Unlike existing works without...

Generative artificial intelligence (GAI) is emerging as a promising solution for the vehicular metaverse due to its adaptable, high-quality, and multi-modal content generation capabilities. Particularly noteworthy is the recent introduction of the Sora model, a Transformer-based diffusion model, which exhibits exceptional performance in visual scen...

Vehicular ad hoc networks (VANETs) establish wireless connections among all vehicles, enabling seamless mobile communication. However, existing conditional privacy protection VANETs authentication schemes fail to address the issue of potential key-exposure and do not provide accelerated vehicle authentication. In this paper, we propose a reputation...

In this paper, based on martingale theory, we investigate the problem of maximum throughput in hybrid energy harvesting wireless communication systems (EH-WCS) under energy storage and delay (or backlog) constraints. Specifically, the energy supply and data transmission of the hybrid EH-WCS are modeled as two queuing systems. For the first energy s...

This paper investigates the secure simultaneous wireless information and power transfer (SWIPT) assisted by the simultaneous transmitting and reflecting reconfigurable intelligent surfaces (STAR-RISs). Specifically, a base station (BS) configured multi-antennas has secure communication demand to an information receiver (IR) and performs wireless po...

Employing massive Mobile AI-Generated Content (AIGC) Service Providers (MASPs) with powerful models, high-quality AIGC services become accessible for resource-constrained end users. However, this advancement, referred to as mobile AIGC, also introduces a significant challenge: users should download large AIGC outputs from the MASPs, leading to subs...

AI agents based on multimodal large language models (LLMs) are expected to revolutionize human-computer interaction, and offer more personalized assistant services across various domains like healthcare, education, manufacturing, and entertainment. Deploying LLM agents in 6G networks enables users to access previously expensive AI assistant service...

Recently, generative AI technologies have emerged as significant advancements in the artificial intelligence field, renowned for their language and image generation capabilities. Meantime, the spaceair- ground integrated network (SAGIN) is an integral part of future B5G/6G for achieving ubiquitous connectivity. Inspired by this, this article explor...

With the impressive generative capabilities of diffusion models, personalized content synthesis has emerged as the most highly anticipated. However, the large model sizes and iterative nature of inference make it difficult to deploy personalized diffusion models broadly on local devices with varying computational power. To this end, we propose a no...

The Internet of Things (IoT) ecosystem is undergoing a significant evolution through its integration with satellite networks, empowering remote and computation-intensive IoT tasks to leverage computing services via satellite links. Current research in this field predominantly focuses on minimizing latency and energy consumption in computation offlo...

The rapid development of generative AI technologies, including large language models (LLMs), has brought transformative changes to various fields. However, deploying such advanced models on mobile and edge devices remains challenging due to their high computational, memory, communication, and energy requirements. To address these challenges, we pro...

Satellite-ground twin networks (SGTNs) are regarded as a promising service paradigm, which can provide mega access services and powerful computation offloading capabilities via cloud-fog automation functions. Specifically, cloud-fog automation technologies are collaboratively leveraged to enable dense connectivity, pervasive computing, and intellig...

With the significant advancements in artificial intelligence (AI) technologies and computational capabilities, generative AI (GAI) has become a pivotal digital content generation technique for offering superior digital services. However, due to the inherent instability of AI models, directing GAI towards the desired output remains a challenging tas...

In the era of 6G, featuring compelling visions of digital twins and metaverses, Extended Reality (XR) has emerged as a vital conduit connecting the digital and physical realms, garnering widespread interest. Ensuring a fully immersive wireless XR experience stands as a paramount technical necessity, demanding the liberation of XR from the confines...

Generative AI (GAI) has emerged as a significant advancement in artificial intelligence, renowned for its language and image generation capabilities. This paper presents "AI-Generated Everything" (AIGX), a concept that extends GAI beyond mere content creation to real-time adaptation and control across diverse technological domains. In networking, A...

In this paper, we investigate a cognitive multicast communication system aided by active reconfigurable intelligent surface (active RIS). Specifically, for an underlay spectrum sharing cognitive multicast network, a cognitive radio base station (CRBS) communicates with secondary users (SUs) assisted by an active RIS. Meanwhile, the interference to...

The integration of semantic communication with mobile edge computing (MEC) has emerged as a prominent research area. In this paper, we explore a novel scenario where semantic communication is integrated with unmanned aerial vehicles (UAVs) to enhance MEC, particularly in the face of jamming attacks. Our research focuses on addressing the resource m...

Updates of extensive Internet of Things (IoT) data are critical to the immersion of vehicular metaverse services. However, providing high-quality and sustainable data in unstable and resource-constrained vehicular networks remains a significant challenge. To address this problem, we put forth a novel immersion-aware model trading framework that inc...

The blockchain can offer a dependable and secure platform for Internet of Things (IoT) transactions with its distributed and secure network architecture. Unfortunately, it faces challenges such as limited throughput, excessive computational costs, and high transaction fees. Off-chain scaling protocols are used to address the scalability of blockcha...

In this paper, we investigate the mmWave beam tracking for vehicle-to-infrastructure (V2I) communications to find the optimal beam via sub-6 GHz channel state information (CSI). We consider two scenarios: 1) sub-6 GHz and mmWave transceivers are co-located on the same base station (BS), and 2) sub-6 GHz and mmWave BSs are separated in different pla...

Intelligent reflecting surface (IRS) can reconfigure the channel conditions, while the passive beamforming gain is limited by the severe double path-loss effect. Fortunately, active IRS (AIRS) is emerging to tackle obstacles by simultaneously adjusting the phase and amplitude of each reflection element. In this paper, we propose an AIRS-assisted un...

Groundbreaking applications such as ChatGPT have heightened research interest in generative artificial intelligence (GAI). Essentially, GAI excels not only in content generation but also signal processing, offering support for wireless sensing. Hence, we introduce a novel GAI-assisted human flow detection system (G-HFD). Rigorously, G-HFD first use...

Vehicle trajectory prediction (VTP) is important for ensuring safe decision-making and planning in Internet of Vehicles (IoV). In complex traffic scenarios, accurate and reliable trajectory prediction requires comprehensive understanding of the interaction behaviors among vehicles. However, existing methods fail to effectively capture vehicle inter...

Mobile multimedia networks (MMNs) demonstrate great potential in delivering low-latency and high-quality entertainment and tactical applications, such as short-video sharing, online conferencing, and battlefield surveillance. For instance, in tactical surveillance of battlefields, scalability and sustainability are indispensable for maintaining lar...

Semantic Communication (SemCom) plays a pivotal role in 6G networks, offering a viable solution for future efficient communication. Deep Learning (DL)-based semantic codecs further enhance this efficiency. However, the vulnerability of DL models to security threats, such as adversarial attacks, poses significant challenges for practical application...

Vehicle-to-everything (V2X) communication supports numerous tasks, from driving safety to entertainment services. To achieve a holistic view, vehicles are typically equipped with multiple sensors to compensate for undetectable blind spots. However, processing large volumes of multi-modal data increases transmission load, while the dynamic nature of...

Cross-Technology Communication (CTC) introduces novel security challenges, demanding urgent mitigation strategies. Although recent literature offers the possibility of detecting malicious CTC, they commonly require access to In-phase and Quadrature (IQ) signals, thus not compatible with existing billions of IoT devices. In this paper, we propose a...

Generative AI (GenAI), exemplified by Large Language Models (LLMs) such as OpenAI's ChatGPT, is revolutionizing various fields. Central to this transformation is Data Center Networking (DCN), which not only provides the computational power necessary for GenAI training and inference but also delivers GenAI-driven services to users. This article exam...

Space-air-ground (SAG) integrated heterogenous networks can provide pervasive intelligence services for various ground users (GUs). The network can help cellular networks release network resources and alleviate congestion pressure. Moreover, one important application of the network is that digital twin (DT) can enable nearly-instant wireless connec...

Artificial Intelligence Generated Content (AIGC) Services have significant potential in digital content creation. The distinctive abilities of AIGC, such as content generation based on minimal input, hold huge potential, especially when integrating with semantic communication (SemCom). In this paper, a novel comprehensive conceptual model for the i...

As Metaverse emerges as the next-generation Internet paradigm, the ability to efficiently generate content is paramount. AI-Generated Content (AIGC) emerges as a key solution, yet the resource-intensive nature of large Generative AI (GAI) models presents challenges. To address this issue, we introduce an AIGC-as-a-Service (AaaS) architecture, which...

AI-Generated Content (AIGC) services are essential in developing the Metaverse, providing various digital content to build shared virtual environments. The services can also offer personalized content with user assistance, making the Metaverse more human-centric. However, user-assisted content creation requires significant communication resources t...

Semantic communication (SemCom) has emerged as a promising architecture in the realm of intelligent communication paradigms. SemCom involves extracting and compressing the core information at the transmitter while enabling the receiver to interpret it based on established knowledge bases (KBs). This approach enhances communication efficiency greatl...

Matchmaking encryption is a method employed to address the security and privacy concerns of cloud-enabled IoT healthcare. Nevertheless, matchmaking encryption technology encounters challenges in effectively implementing critical functionalities, such as resolving a single-key-exposure problem, achieving secure short-epoch communication, and simulta...

Semantic Communication (SemCom) is envisaged as the next-generation paradigm to address challenges stemming from the conflicts between the increasing volume of transmission data and the scarcity of spectrum resources. However, existing SemCom systems face drawbacks, such as low explainability, modality rigidity, and inadequate reconstruction functi...

Due to the growing number of satellites and the deployment of onboard computing hardware and network virtualization technologies on satellites, topologies and resources in satellite networks (SNs) change frequently, making it difficult for temporal graph models to support continuous service provisioning for diversified applications. In this letter,...

The rapid proliferation of Internet of Things (IoT) devices and the deployment of edge computing infrastructures have significantly advanced data processing and network communications. Federated Learning (FL), leveraging these developments , offers a decentralized approach to learning across edge devices while preserving data privacy. However, trad...

The surge in connected devices in 6G with typical massive access scenarios, such as smart agriculture, and smart cities, poses significant challenges to unsustainable traditional communication with limited radio resources and already high system complexity. Fortunately, the booming artificial intelligence technology and the growing computational po...

Voltage stability remains a pivotal concern in power systems, especially with the integration of renewable energy sources and high-demand loads that use induction motors. Recent blackouts have highlighted the vulnerability of wind power systems to voltage stability assessment (VSA) threats. Traditional machine learning-based VSA methods, while effi...

With the rapid development of maritime activities, efficient and reliable maritime communications have attracted ever-increasing attention, and mounting reconfigurable intelligent surface (RIS) on unmanned aerial vehicle (UAV), called UAV-RIS, can provide flexible and adaptable services for maritime communications. In this paper, we investigate a U...

In recent years, jointly optimizing unmanned aerial vehicle (UAV) hover point selection and resource management for UAV-assisted mobile edge computing (MEC) is a hot research topic. Unlike previous studies, this paper investigates the optimization problem of hover point selection and resource management under dynamic jamming attacks, where the obje...

In this paper, we study a joint computation offloading and resource allocation optimization problem for the intelligent reflecting surface (IRS)-assisted mobile edge computing (MEC) system. Specifically, we consider an IRS-assisted multi-device MEC system, where mobile devices (MDs) can either execute the computation-intensive tasks locally or offl...

Due to the open accessibility of wireless networks with severe privacy risks, covert communication has gained increasing attention, where the effective range is limited by the low transmit power. Fortunately, employing intelligent reflecting surface (IRS) as a relay has become an appealing solution to extend the range of covert communication. To th...

As a fundamental component of Internet of Things (IoT) devices, firmware plays an essential role. Nowadays, the development of IoT firmware relies extensively on third-party components and substantially enhances development efficiency. However, these components are not inherently secure, and their vulnerabilities can adversely affect the security o...

With the phenomenal success of diffusion models and ChatGPT, deep generation models (DGMs) have been experiencing explosive growth. Not limited to content generation, DGMs are also widely adopted in Internet of Things, Metaverse, and digital twin, due to their outstanding ability to represent complex patterns and generate realistic samples. In this...

Advancements in artificial intelligence (AI), and the surge in diverse training data, have facilitated AI generated content (AIGC). Despite high efficiency, the inherent instability of AI models poses challenges in creating user-specific content, especially when creating an avatar for a user. To address this issue, this article integrates wireless...

In this letter, we investigate network slicing strategy for real-time applications over large-scale satellite networks (SNs) with heterogeneous transceivers. We identify that the slicing problem over the time-varying SNs with heterogeneous transceivers can be formulated as an integer linear programming problem. A branch and bound method for solving...

Unmanned aerial vehicle (UAV) swarms have found extensive applications owing to their flexibility, mobility, cost-effectiveness, and capacity for collaborative and autonomous service delivery. Empowered by intelligent algorithms, UAV swarm can exhibit cohesive behaviors and autonomously coordinate to achieve collective objectives. Nonetheless, in r...

The rapidly evolving field of generative artificial intelligence technology has introduced innovative approaches for developing semantic communication (SemCom) frameworks, leading to the emergence of a new paradigm-generative SemCom (GSC). However, the complex processes involved in semantic extraction and generative inference may result in consider...

The increasing demand for sensing, collecting, transmitting, and processing vast amounts of data poses significant challenges for resource-constrained mobile users, thereby impacting the performance of wireless networks. In this regard, from a case of mobile crowdsensing (MCS), we aim at leveraging attention mechanisms in machine learning approache...

Task scheduling in large-scale industrial Internet of Things (IIoT) is characterized by the presence of diverse resources and the requirement for efficient and synchronized processing across distributed edge clouds, raising a significant challenge. This paper proposes a task scheduling framework across edge clouds, namely LsiA3CS, which employs dee...