Hongyang Du

Hongyang Du
The University of Hong Kong | HKU

Doctor of Philosophy

About

247
Publications
36,415
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3,750
Citations
Introduction

Publications

Publications (247)
Article
With the continuous advancement of network technology, various emerging complex networking optimization problems have created a wide range of applications utilizing game theory. However, since game theory is a mathematical framework, game theory-based solutions often rely heavily on the experience and knowledge of human experts. Recently, the remar...
Preprint
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The rapid advances in generative artificial intelligence (GenAI) have revolutionized AI applications, raising critical concerns regarding privacy, ethical use, and data ownership. With the growing emphasis on concepts such as the "right to be forgotten," the ability to selectively remove or "unlearn" specific training data is emerging as a fundamen...
Preprint
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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...
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The rapid advancement of immersive technologies has propelled the development of the Metaverse, where the convergence of virtual and physical realities necessitates the generation of high-quality, photorealistic images to enhance user experience. However, generating these images, especially through Generative Diffusion Models (GDMs), in mobile edge...
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With advancements in physical power systems and network technologies, integrated Cyber-Physical Power Systems (CPPS) have significantly enhanced system monitoring and control efficiency and reliability. This integration, however, introduces complex challenges in designing coherent CPPS, particularly as few studies concurrently address the deploymen...
Preprint
Emerging technologies in sixth generation (6G) of wireless communications, such as terahertz communication and ultra-massive multiple-input multiple-output, present promising prospects. Despite the high data rate potential of millimeter wave communications, millimeter wave (mmWave) communications in urban low altitude economy (LAE) environments are...
Preprint
Multi-access edge computing (MEC) is emerging as a promising paradigm to provide flexible computing services close to user devices (UDs). However, meeting the computation-hungry and delay-sensitive demands of UDs faces several challenges, including the resource constraints of MEC servers, inherent dynamic and complex features in the MEC system, and...
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This paper investigates adaptive transmission strategies in embodied AI-enhanced vehicular networks by integrating large language models (LLMs) for semantic information extraction and deep reinforcement learning (DRL) for decision-making. The proposed framework aims to optimize both data transmission efficiency and decision accuracy by formulating...
Article
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By integrating Artificial Intelligence (AI) with the Internet of Things (IoT), Artificial Intelligence of Things (AIoT) has revolutionized many fields. However, AIoT is facing the challenges of energy consumption and carbon emissions due to the continuous advancement of mobile technology. Fortunately, Generative AI (GAI) holds immense potential to...
Article
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...
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As a form of artificial intelligence (AI) technology based on interactive learning, deep reinforcement learning (DRL) has been widely applied across various fields and has achieved remarkable accomplishments. However, DRL faces certain limitations, including low sample efficiency and poor generalization. Therefore, in this article, we show how to l...
Article
With the extensive adoption of information technology, tunnel construction is experiencing a rapid digital transformation. Integrating powerful direct communication among construction equipment (CE) facilitates real-time data exchange, promoting collaborative operations among CE. Concurrent execution of multiple construction procedures leads to a s...
Article
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...
Article
Coordinated multi-base station (BS) transmission has emerged as a fundamental access technology to augment network capability and improve spectrum efficiency. However, the computation-intensive feedback of channel state information (CSI) poses significant challenges in determining physical-layer parameters for coordinated BSs. In this paper, we inv...
Article
The development of B5G and 6G technologies has led to an explosive growth in device connectivity density in Industrial Internet of Things (IIoT) systems. However, the limited spectrum resources in industrial wireless networks pose significant challenges for large-scale access and communication rates, especially for factory automation applications t...
Article
Extremely large-scale multiple-input-multiple-output (XL-MIMO) is an emerging transceiver technology for enabling next-generation communication systems, due to its potential for substantial enhancement in both the spectral efficiency and spatial resolution. However, the achievable performance limits of various promising XL-MIMO configurations have...
Preprint
This paper delves into the applications of generative artificial intelligence (GAI) in semantic communication (SemCom) and presents a thorough study. Three popular SemCom systems enabled by classical GAI models are first introduced, including variational autoencoders, generative adversarial networks, and diffusion models. For each system, the funda...
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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...
Preprint
Unmanned aerial vehicles (UAVs) can be utilized as relay platforms to assist maritime wireless communications. However, complex channels and multipath effects at sea can adversely affect the quality of UAV transmitted signals. Collaborative beamforming (CB) can enhance the signal strength and range to assist the UAV relay for remote maritime commun...
Conference Paper
Container-based microservices are ideal for service provisioning due to their lightweight deployment and fast startup time, enabling them to be well-suited for resource-limited edge cloud networks. Furthermore, the inherent layered structure of containers provides a powerful mechanism to address the resource constraints of computing nodes through e...
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Large Language Models (LLMs) have demonstrated remarkable capabilities in various tasks, leading to their increasing adoption in diverse services delivered through wireless networks. There is a growing trend toward longer prompts to better leverage LLMs' capabilities and address difficult tasks. However, longer prompts not only increase data transm...
Article
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,...
Article
The integration of semantic communication with Internet of Things (IoT) technologies has advanced the development of Semantic IoT (SIoT), with edge mobile networks playing an increasingly vital role. This paper presents a framework for SIoT-based image retrieval services, focusing on the application in automotive market analysis. Here, semantic inf...
Article
Federated learning (FL) has been vigorously promoted in wireless edge networks as it fosters collaborative training of machine learning (ML) models while preserving individual user privacy and data security. In conventional FL, user equipment (UE) and an aggregator can collaboratively train shared global ML models by transmitting interactive ML mod...
Article
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...
Article
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...
Article
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...
Article
In response to the needs of 6G global communications, satellite communication networks have emerged as a key solution. However, the large-scale development of satellite communication networks is constrained by complex system models, whose modeling is challenging for massive users. Moreover, transmission interference between satellites and users ser...
Article
Federated learning (FL) opens a new promising paradigm for the Industrial Internet of Things (IoT) since it can collaboratively train machine learning models without sharing private data. However, deploying FL frameworks in real IoT scenarios faces three critical challenges, i.e. , statistical heterogeneity, resource constraint, and fairness. To...
Preprint
Large Language Models (LLMs) have demonstrated remarkable capabilities in various tasks, leading to their increasing deployment in wireless networks for a wide variety of user services. However, the growing longer prompt setting highlights the crucial issue of computational resource demands and huge communication load. To address this challenge, we...
Preprint
With the rapid advancement of artificial intelligence (AI), generative AI (GenAI) has emerged as a transformative tool, enabling customized and personalized AI-generated content (AIGC) services. However, GenAI models with billions of parameters require substantial memory capacity and computational power for deployment and execution, presenting sign...
Preprint
Cloud computing and edge/fog computing are playing a pivotal role in driving the transformation of industrial cyber-physical systems (ICPS) towards greater intelligence and automation by providing high-quality computation offloading services to Internet of Things devices (IoTDs). Recently, space-air-ground integrated multi-access edge computing (SA...
Preprint
Generative AI (GenAI) has emerged as a transformative technology, enabling customized and personalized AI-generated content (AIGC) services. In this paper, we address challenges of edge-enabled AIGC service provisioning, which remain underexplored in the literature. These services require executing GenAI models with billions of parameters, posing s...
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Score-based generative models can effectively learn the distribution of data by estimating the gradient of the distribution. Due to the multi-step denoising characteristic, researchers have recently considered combining score-based generative models with the gradient boosting algorithm, a multi-step supervised learning algorithm, to solve supervise...
Article
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Mobile artificial intelligence-generated content (AIGC) refers to the adoption of generative artificial intelligence (GAI) algorithms deployed at mobile edge networks to automate the information creation process while fulfilling the requirements of end users. Mobile AIGC has recently attracted phenomenal attentions and can be a key enabling technol...
Article
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...
Article
The development of the mobile Metaverse has garnered increasing attention in the next-generation Internet, fueled by the rapid advancements of mobile Internet, communication, and computing technologies. With the resource limitations faced by mobile Metaverse users (MUs), the mobile Metaverse market is flourishing. This market enables MUs to access...
Article
With the advance of artificial intelligence (AI), the concept of interactive AI (IAI) has been introduced, which can interactively understand and respond not only to human user input but also to dynamic system and network conditions. In this article, we explore an integration and enhancement of IAI in networking.We first comprehensively review rece...
Article
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...
Article
This paper investigates artificial intelligence (AI) empowered schemes for reconfigurable intelligent surface (RIS) assisted networks from the perspective of fast implementation. We formulate a weighted sum-rate maximization problem for a multi-RIS-assisted network. To avoid huge channel estimation overhead due to activate all RISs, we propose a co...
Article
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The Internet of things (IoT) can significantly enhance the quality of human life, specifically in healthcare, attracting extensive attentions to IoT-healthcare services. Meanwhile, the human digital twin (HDT) is proposed as an innovative paradigm that can comprehensively characterize the replication of the individual human body in the digital worl...
Article
5G and Beyond 5G communication technologies have promoted the architectural innovation of the Industrial Internet of Things (IIoT) and the wide application of edge learning. As Beyond 5G technologies enhance wireless communication within IIoT, the demand for efficient, secure data management becomes paramount. Edge learning emerges as a solution fo...
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This paper studies an efficient multimodal data communication scheme for video conferencing. In our considered system, a speaker gives a talk to the audiences, with talking head video and audio being transmitted. Since the speaker does not frequently change posture and high-fidelity transmission of audio (speech and music) is required, redundant vi...
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In wireless networks, applying deep learning models to solve matching problems between different entities has become a mainstream and effective approach. However, the complex network topology in 6G multiple access presents significant challenges for the real-time performance and stability of matching generation. Generative artificial intelligence (...
Article
In recent years, electric vehicles have emerged as a promising mode of transportation. With the development of Internet of Robotic Things (IoRT) technology, charging stations are employing interconnected robots to charge electric vehicles, automating the collection and transmission of user charging information. However, charging processes pose risk...
Article
The flexible-position multiple-input multiple-output (FLP-MIMO) -- used in, for example, fluid antennas and movable antennas -- is a promising technology for future wireless communications. This is due to the fact that the positions of antennas at the transceiver and reflector can be dynamically optimized using FLP-MIMO to achieve better channel co...
Article
With the growing popularity of wearable devices, body-centric networks have become the focus of Internet of Things (IoT) research. However, malicious eavesdroppers and attackers pose threats to user privacy and network secrecy. Fortunately, physical layer security (PLS) communication and covert communication (CC) have been introduced and can be use...
Article
Distributed machine learning is becoming increasingly popular for geo-distributed data analytics, facilitating the collaborative analysis of data scattered across data centers in different regions. This paradigm eliminates the need for centralizing sensitive raw data in one location but faces the significant challenge of high parameter synchronizat...
Article
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...
Article
Extremely large-scale multiple-input-multiple-output (XL-MIMO) is a promising technology to achieve high spectral efficiency (SE) and energy efficiency (EE) in future wireless systems. The larger array aperture of XL-MIMO makes communication scenarios closer to the near-field region. Therefore, near-field resource allocation is essential in realizi...
Article
As generative artificial intelligence (GAI) models continue to evolve, their generative capabilities are increasingly enhanced, and being used extensively in content generation. Furthermore, GAI also excels in data modeling and analysis, benefiting wireless communication systems. In this article, we investigate applications of GAI in the physical l...
Preprint
For millimeter-wave (mmWave) non-orthogonal multiple access (NOMA) communication systems, we propose an innovative near-field (NF) transmission framework based on dynamic metasurface antenna (DMA) technology. In this framework, a base station (BS) utilizes the DMA hybrid beamforming technology combined with the NOMA principle to maximize communicat...
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With the advancement of generative artificial intelligence (GenAI) models, their capability to generate content is seeing significant enhancement, leading to widespread applications in the field of data generation and forecasting. Furthermore, GenAI has strong capabilities in data modeling and analysis, which enhances Internet of electric vehicles...
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Cell-free (CF) massive multiple-input multipleoutput (MIMO) provides a ubiquitous coverage to user equipments (UEs) but it is also susceptible to interference. Ratesplitting (RS) effectively extracts data by decoding interference, yet its effectiveness is limited by the weakest UE. In this paper, we investigate an RS-based CF massive MIMO system, w...
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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...
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In this letter, we present a diffusion model method for signal detection in near-field communication with unknown noise characteristics. We consider an uplink transmission of a near-filed MIMO communication system consisting of multiple mobile terminals and one base station with multiple antennas. Then, we proposed a Maximum Likelihood Estimation D...
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Booming time-critical services, such as automated manufacturing and remote operations, stipulate increasing demands for facilitating large-scale Industrial Internet of Things (IoT). Recently, a cycle specified queuing and forwarding (CSQF) scheme has been advocated to enhance the Ethernet. However, CSQF only outlines a foundational equipment-level...
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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...
Article
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...
Article
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...
Article
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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...
Article
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...
Article
As indoor applications grow in diversity, wireless sensing, vital in areas like localization and activity recognition, is attracting renewed interest. Indoor wireless sensing relies on signal processing, particularly channel state information (CSI) based signal parameter estimation. Nonetheless, regarding reflected signals induced by dynamic human...
Article
Generative Diffusion Models (GDMs) have emerged as potent tools for generating high-quality, creative content across various media, including audio, images, videos, and 3D models. Their application in AI-Generated Content (AIGC) marks a pivotal advancement in the evolution from the Internet of Things (IoT) to the Artificial Intelligence of Things (...
Preprint
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Integrated sensing and communications (ISAC) is expected to be a key technology for 6G, and channel state information (CSI) based sensing is a key component of ISAC. However, current research on ISAC focuses mainly on improving sensing performance, overlooking security issues, particularly the unauthorized sensing of users. In this paper, we propos...
Preprint
Internet of Things (IoT) devices are typically powered by small-sized batteries with limited energy storage capacity, requiring regular replacement or recharging. To reduce costs and maintain connectivity in IoT networks, energy harvesting technologies are regarded as a promising solution. Notably, due to its robust analytical and generative capabi...
Article
Cell-free massive multiple-input multiple-output (mMIMO) and extremely large-scale MIMO (XL-MIMO) are regarded as promising innovations for the forthcoming generation of wireless communication systems. Their significant advantages in augmenting the number of degrees of freedom have garnered considerable interest. In this article, we first review th...
Article
The deep reinforcement learning-based transmission design for reconfigurable intelligent surface (RIS) assisted multiple input single output networks is investigated in this research. An energy efficiency (EE) maximization problem is formulated under constraints of the rate requirement, the power budget and the phase shift coefficient. To be adapta...
Article
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...
Article
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...
Conference Paper
Federated unlearning has emerged as a promising paradigm to erase the client-level data effect without affecting the performance of collaborative learning models. However, the federated unlearning process often introduces extensive storage overhead and consumes substantial computational resources, thus hindering its implementation in practice. To a...
Article
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As the next-generation wireless communication system, sixth-generation (6G) technologies are emerging, enabling various mobile edge networks that can revolutionize wireless communication and connectivity. By integrating generative artificial intelligence (GAI) with mobile edge networks, generative mobile edge networks possess immense potential to e...
Preprint
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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...
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Traffic flow estimation (TFE) is crucial for intelligent transportation systems. Traditional TFE methods rely on extensive road sensor networks and typically incur significant costs. Sparse mobile crowdsensing enables a cost-effective alternative by utilizing sparsely distributed probe vehicle data (PVD) provided by connected vehicles. However, as...
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The vehicular metaverse is envisioned as a blended immersive domain that promises to bring revolutionary changes to the automotive industry. As a core component of vehicular metaverses, Vehicle Twins (VTs) are digital twins that cover the entire life cycle of vehicles, providing immersive virtual services for Vehicular Metaverse Users (VMUs). Vehic...
Article
Recognizing the tremendous improvements that the integration of generative AI can bring to intelligent transportation systems, this article explores the integration of generative AI technologies in vehicular networks, focusing on their potential applications and challenges. Generative AI, with its capabilities of generating realistic data and facil...
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In the rapidly evolving Next-Generation Networking (NGN) era, the adoption of zero-trust architectures has become increasingly crucial to protect security. However, provisioning zero-trust services in NGNs poses significant challenges, primarily due to the environmental complexity and dynamics. Motivated by these challenges, this paper explores eff...
Article
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The synergy between Unmanned Aerial Vehicles (UAVs) and metaverses is giving rise to an emerging paradigm named UAV metaverses, which create a unified ecosystem that blends physical and virtual spaces, transforming drone interaction and virtual exploration. UAV Twins (UTs), as the digital twins of UAVs that revolutionize UAV applications by making...
Article
Lightweight training and distributed tiny data storage in local model will lead to the severe challenge of convergence for tiny federated learning (FL). Achieving fast convergence in tiny FL is crucial for many emerging applications in Internet of Unmanned Aerial Vehicles (IUAVs) networks. Excessive information exchange between UAVs and IoT devices...
Preprint
The rapid advancement of Artificial Intelligence (AI) has introduced Deep Neural Network (DNN)-based tasks to the ecosystem of vehicular networks. These tasks are often computation-intensive, requiring substantial computation resources, which are beyond the capability of a single vehicle. To address this challenge, Vehicular Edge Computing (VEC) ha...
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With the rapid proliferation of mobile devices and data, next-generation wireless communication systems face stringent requirements for ultra-low latency, ultra-high reliability, and massive connectivity. Traditional AI-driven wireless network designs, while promising, often suffer from limitations such as dependency on labeled data and poor genera...