Search Results for author: Zehui Xiong

Found 44 papers, 3 papers with code

Generative AI-aided Joint Training-free Secure Semantic Communications via Multi-modal Prompts

no code implementations5 Sep 2023 Hongyang Du, Guangyuan Liu, Dusit Niyato, Jiayi Zhang, Jiawen Kang, Zehui Xiong, Bo Ai, Dong In Kim

The system jointly optimizes the diffusion step, jamming, and transmitting power with the aid of the generative diffusion models, enabling successful and secure transmission of the source messages.

Artificial Intelligence for Web 3.0: A Comprehensive Survey

no code implementations17 Aug 2023 Meng Shen, Zhehui Tan, Dusit Niyato, Yuzhi Liu, Jiawen Kang, Zehui Xiong, Liehuang Zhu, Wei Wang, Xuemin, Shen

Then, we thoroughly analyze the current state of AI technology applications in the four layers of Web 3. 0 and offer some insights into its potential future development direction.


Vision-based Semantic Communications for Metaverse Services: A Contest Theoretic Approach

no code implementations15 Aug 2023 Guangyuan Liu, Hongyang Du, Dusit Niyato, Jiawen Kang, Zehui Xiong, Boon Hee Soong

The framework provides a novel solution to resource allocation for avatar association in VR environments, ensuring a smooth and immersive experience for all users.

Blockchain-empowered Federated Learning for Healthcare Metaverses: User-centric Incentive Mechanism with Optimal Data Freshness

no code implementations29 Jul 2023 Jiawen Kang, Jinbo Wen, Dongdong Ye, Bingkun Lai, Tianhao Wu, Zehui Xiong, Jiangtian Nie, Dusit Niyato, Yang Zhang, Shengli Xie

Given the revolutionary role of metaverses, healthcare metaverses are emerging as a transformative force, creating intelligent healthcare systems that offer immersive and personalized services.

Decision Making Federated Learning +1

Multi-Agent Deep Reinforcement Learning for Dynamic Avatar Migration in AIoT-enabled Vehicular Metaverses with Trajectory Prediction

no code implementations26 Jun 2023 Junlong Chen, Jiawen Kang, Minrui Xu, Zehui Xiong, Dusit Niyato, Chuan Chen, Abbas Jamalipour, Shengli Xie

Specifically, we propose a model to predict the future trajectories of intelligent vehicles based on their historical data, indicating the future workloads of RSUs. Based on the expected workloads of RSUs, we formulate the avatar task migration problem as a long-term mixed integer programming problem.

Trajectory Prediction

STAR-RIS-Assisted Privacy Protection in Semantic Communication System

no code implementations22 Jun 2023 Yiru Wang, Wanting Yang, Pengxin Guan, Yuping Zhao, Zehui Xiong

Semantic communication (SemCom) has emerged as a promising architecture in the realm of intelligent communication paradigms.

Intelligent Communication

Adversarial Attacks and Defenses for Semantic Communication in Vehicular Metaverses

no code implementations6 Jun 2023 Jiawen Kang, Jiayi He, Hongyang Du, Zehui Xiong, Zhaohui Yang, Xumin Huang, Shengli Xie

In this article, we propose a hierarchical SemCom-enabled vehicular metaverses framework consisting of the global metaverse, local metaverses, SemCom module, and resource pool.

DADFNet: Dual Attention and Dual Frequency-Guided Dehazing Network for Video-Empowered Intelligent Transportation

no code implementations19 Apr 2023 Yu Guo, Ryan Wen Liu, Jiangtian Nie, Lingjuan Lyu, Zehui Xiong, Jiawen Kang, Han Yu, Dusit Niyato

To eliminate the influences of adverse weather conditions, we propose a dual attention and dual frequency-guided dehazing network (termed DADFNet) for real-time visibility enhancement.

Management object-detection +1

Deep Generative Model and Its Applications in Efficient Wireless Network Management: A Tutorial and Case Study

no code implementations30 Mar 2023 Yinqiu Liu, Hongyang Du, Dusit Niyato, Jiawen Kang, Zehui Xiong, Dong In Kim, Abbas Jamalipour

With the phenomenal success of diffusion models and ChatGPT, deep generation models (DGMs) have been experiencing explosive growth from 2022.


Guiding AI-Generated Digital Content with Wireless Perception

no code implementations26 Mar 2023 Jiacheng Wang, Hongyang Du, Dusit Niyato, Zehui Xiong, Jiawen Kang, Shiwen Mao, Xuemin, Shen

Experiments results verify the effectiveness of the WP-AIGC framework, highlighting its potential as a novel approach for guiding AI models in the accurate generation of digital content.

AI-Generated Incentive Mechanism and Full-Duplex Semantic Communications for Information Sharing

1 code implementation3 Mar 2023 Hongyang Du, Jiacheng Wang, Dusit Niyato, Jiawen Kang, Zehui Xiong, Dong In Kim

Specifically, a user can transmit the generated content and semantic information extracted from their view image to nearby users, who can then use this information to obtain the spatial matching of computation results under their view images.

Mixed Reality

Generative AI-empowered Simulation for Autonomous Driving in Vehicular Mixed Reality Metaverses

no code implementations16 Feb 2023 Minrui Xu, Dusit Niyato, Junlong Chen, Hongliang Zhang, Jiawen Kang, Zehui Xiong, Shiwen Mao, Zhu Han

In the vehicular mixed reality (MR) Metaverse, the distance between physical and virtual entities can be overcome by fusing the physical and virtual environments with multi-dimensional communications in autonomous driving systems.

Autonomous Driving Mixed Reality

Generative AI-empowered Effective Physical-Virtual Synchronization in the Vehicular Metaverse

no code implementations18 Jan 2023 Minrui Xu, Dusit Niyato, Hongliang Zhang, Jiawen Kang, Zehui Xiong, Shiwen Mao, Zhu Han

Furthermore, we propose a multi-task enhanced auction-based mechanism to match and price AVs and MARs for RSUs to provision real-time and effective services.

Autonomous Vehicles

Enabling AI-Generated Content (AIGC) Services in Wireless Edge Networks

no code implementations9 Jan 2023 Hongyang Du, Zonghang Li, Dusit Niyato, Jiawen Kang, Zehui Xiong, Xuemin, Shen, Dong In Kim

To achieve efficient AaaS and maximize the quality of generated content in wireless edge networks, we propose a deep reinforcement learning-enabled algorithm for optimal ASP selection.

When Quantum Information Technologies Meet Blockchain in Web 3.0

no code implementations29 Nov 2022 Minrui Xu, Xiaoxu Ren, Dusit Niyato, Jiawen Kang, Chao Qiu, Zehui Xiong, Xiaofei Wang, Victor C. M. Leung

Therefore, in this paper, we introduce a quantum blockchain-driven Web 3. 0 framework that provides information-theoretic security for decentralized data transferring and payment transactions.

Cloud Computing

Performance Analysis of Free-Space Information Sharing in Full-Duplex Semantic Communications

no code implementations27 Nov 2022 Hongyang Du, Jiacheng Wang, Dusit Niyato, Jiawen Kang, Zehui Xiong, Dong In Kim, Boon Hee Soong

In this paper, we propose a free-space information sharing mechanism based on full-duplex device-to-device (D2D) semantic communications.

Mixed Reality

Semantic Communications for Wireless Sensing: RIS-aided Encoding and Self-supervised Decoding

no code implementations23 Nov 2022 Hongyang Du, Jiacheng Wang, Dusit Niyato, Jiawen Kang, Zehui Xiong, Junshan Zhang, Xuemin, Shen

To select the task-related signal spectrums for achieving efficient encoding, a semantic hash sampling method is introduced.

Self-Supervised Learning

Multi-Resource Allocation for On-Device Distributed Federated Learning Systems

no code implementations1 Nov 2022 Yulan Gao, Ziqiang Ye, Han Yu, Zehui Xiong, Yue Xiao, Dusit Niyato

This work poses a distributed multi-resource allocation scheme for minimizing the weighted sum of latency and energy consumption in the on-device distributed federated learning (FL) system.

Federated Learning

Personalized Saliency in Task-Oriented Semantic Communications: Image Transmission and Performance Analysis

no code implementations25 Sep 2022 Jiawen Kang, Hongyang Du, Zonghang Li, Zehui Xiong, Shiyao Ma, Dusit Niyato, Yuan Li

Semantic communication, as a promising technology, has emerged to break through the Shannon limit, which is envisioned as the key enabler and fundamental paradigm for future 6G networks and applications, e. g., smart healthcare.

Image Retrieval Retrieval

Attention-aware Resource Allocation and QoE Analysis for Metaverse xURLLC Services

2 code implementations10 Aug 2022 Hongyang Du, Jiazhen Liu, Dusit Niyato, Jiawen Kang, Zehui Xiong, Junshan Zhang, Dong In Kim

Although conventional ultra-reliable and low-latency communications (URLLC) can satisfy objective KPIs, it is difficult to provide a personalized immersive experience that is a distinctive feature of the Metaverse.

Economics of Semantic Communication System: An Auction Approach

no code implementations2 Aug 2022 Zi Qin Liew, Hongyang Du, Wei Yang Bryan Lim, Zehui Xiong, Dusit Niyato, Chunyan Miao, Dong In Kim

The proposed incentive mechanism helps to maximize the revenue of semantic model providers in the semantic model trading, and effectively incentivizes model providers to participate in the development of semantic communication systems.

Exploring Attention-Aware Network Resource Allocation for Customized Metaverse Services

1 code implementation31 Jul 2022 Hongyang Du, Jiacheng Wang, Dusit Niyato, Jiawen Kang, Zehui Xiong, Xuemin, Shen, Dong In Kim

With the help of UOAL, we propose an attention-aware network resource allocation algorithm that has two steps, i. e., attention prediction and QoE maximization.

Incentive Mechanism Design for Joint Resource Allocation in Blockchain-based Federated Learning

no code implementations18 Feb 2022 Zhilin Wang, Qin Hu, Ruinian Li, Minghui Xu, Zehui Xiong

Since each client has a limited amount of computing resources, the problem of allocating computing resources into training and mining needs to be carefully addressed.

Federated Learning

Robust Semi-supervised Federated Learning for Images Automatic Recognition in Internet of Drones

no code implementations3 Jan 2022 Zhe Zhang, Shiyao Ma, Zhaohui Yang, Zehui Xiong, Jiawen Kang, Yi Wu, Kejia Zhang, Dusit Niyato

This emerging technology relies on sharing ground truth labeled data between Unmanned Aerial Vehicle (UAV) swarms to train a high-quality automatic image recognition model.

Federated Learning Privacy Preserving

A Contract Theory based Incentive Mechanism for Federated Learning

no code implementations12 Aug 2021 Mengmeng Tian, Yuxin Chen, YuAn Liu, Zehui Xiong, Cyril Leung, Chunyan Miao

It is challenging to design proper incentives for the FL clients due to the fact that the task is privately trained by the clients.

Federated Learning

Joint Transmit Precoding and Reflect Beamforming Design for IRS-Assisted MIMO Cognitive Radio Systems

no code implementations2 Feb 2021 Weiheng Jiang, Yu Zhang, Jun Zhao, Zehui Xiong, Zhiguo Ding

Cognitive radio (CR) is an effective solution to improve the spectral efficiency (SE) of wireless communications by allowing the secondary users (SUs) to share spectrum with primary users (PUs).

Information Theory Signal Processing Information Theory

Intelligent Reflecting Surface Assisted Anti-Jamming Communications Based on Reinforcement Learning

no code implementations23 Dec 2020 Helin Yang, Zehui Xiong, Jun Zhao, Dusit Niyato, Qingqing Wu, Massimo Tornatore, Stefano Secci

Aiming to enhance the communication performance against smart jammer, an optimization problem for jointly optimizing power allocation at the base station (BS) and reflecting beamforming at the IRS is formulated.

reinforcement-learning Reinforcement Learning (RL)

Resource Allocation for Intelligent Reflecting Surface Aided Cooperative Communications

no code implementations18 Dec 2020 Yulan Gao, Chao Yong, Zehui Xiong, Dusit Niyato, Yue Xiao, Jun Zhao

This paper investigates an intelligent reflecting surface (IRS) aided cooperative communication network, where the IRS exploits large reflecting elements to proactively steer the incident radio-frequency wave towards destination terminals (DTs).

Cross-Layer Coordinated Attacks on Cyber-Physical Systems: A LQG Game Framework with Controlled Observations

no code implementations4 Dec 2020 Yunhan Huang, Zehui Xiong, Quanyan Zhu

On the other hand, the interactions between the attacker and the defender in the physical layer significantly impact the observation and jamming strategies.

Privacy-Preserving Federated Learning for UAV-Enabled Networks: Learning-Based Joint Scheduling and Resource Management

no code implementations28 Nov 2020 Helin Yang, Jun Zhao, Zehui Xiong, Kwok-Yan Lam, Sumei Sun, Liang Xiao

However, due to the privacy concerns of devices and limited computation or communication resource of UAVs, it is impractical to send raw data of devices to UAV servers for model training.

Distributed Computing Federated Learning +3

Scalable and Communication-efficient Decentralized Federated Edge Learning with Multi-blockchain Framework

no code implementations10 Aug 2020 Jiawen Kang, Zehui Xiong, Chunxiao Jiang, Yi Liu, Song Guo, Yang Zhang, Dusit Niyato, Cyril Leung, Chunyan Miao

This framework can achieve scalable and flexible decentralized FEL by individually manage local model updates or model sharing records for performance isolation.

Cryptography and Security

Deep Anomaly Detection for Time-series Data in Industrial IoT: A Communication-Efficient On-device Federated Learning Approach

no code implementations19 Jul 2020 Yi Liu, Sahil Garg, Jiangtian Nie, Yang Zhang, Zehui Xiong, Jiawen Kang, M. Shamim Hossain

Third, to adapt the proposed framework to the timeliness of industrial anomaly detection, we propose a gradient compression mechanism based on Top-\textit{k} selection to improve communication efficiency.

Anomaly Detection Federated Learning +2

Joint Auction-Coalition Formation Framework for Communication-Efficient Federated Learning in UAV-Enabled Internet of Vehicles

no code implementations13 Jul 2020 Jer Shyuan Ng, Wei Yang Bryan Lim, Hong-Ning Dai, Zehui Xiong, Jianqiang Huang, Dusit Niyato, Xian-Sheng Hua, Cyril Leung, Chunyan Miao

The simulation results show that the grand coalition, where all UAVs join a single coalition, is not always stable due to the profit-maximizing behavior of the UAVs.

Networking and Internet Architecture Signal Processing

Federated Learning for 6G Communications: Challenges, Methods, and Future Directions

no code implementations4 Jun 2020 Yi Liu, Xingliang Yuan, Zehui Xiong, Jiawen Kang, Xiaofei Wang, Dusit Niyato

As the 5G communication networks are being widely deployed worldwide, both industry and academia have started to move beyond 5G and explore 6G communications.

Federated Learning

Towards Federated Learning in UAV-Enabled Internet of Vehicles: A Multi-Dimensional Contract-Matching Approach

no code implementations8 Apr 2020 Wei Yang Bryan Lim, Jianqiang Huang, Zehui Xiong, Jiawen Kang, Dusit Niyato, Xian-Sheng Hua, Cyril Leung, Chunyan Miao

Coupled with the rise of Deep Learning, the wealth of data and enhanced computation capabilities of Internet of Vehicles (IoV) components enable effective Artificial Intelligence (AI) based models to be built.

Signal Processing Networking and Internet Architecture

Deep Reinforcement Learning Based Intelligent Reflecting Surface for Secure Wireless Communications

no code implementations27 Feb 2020 Helin Yang, Zehui Xiong, Jun Zhao, Dusit Niyato, Liang Xiao, Qingqing Wu

As the system is highly dynamic and complex, and it is challenging to address the non-convex optimization problem, a novel deep reinforcement learning (DRL)-based secure beamforming approach is firstly proposed to achieve the optimal beamforming policy against eavesdroppers in dynamic environments.

reinforcement-learning Reinforcement Learning (RL)

Reconfigurable Intelligent Surface Aided Power Control for Physical-Layer Broadcasting

no code implementations7 Dec 2019 Huimei Han, Jun Zhao, Zehui Xiong, Dusit Niyato, Wenchao Zhai, Marco Di Renzo, Quoc-Viet Pham, Weidang Lu

Our goalis to minimize the transmit power at the BS by jointly designing the transmit beamforming at the BSand the phase shifts of the passive elements at the RIS.

Reliable Federated Learning for Mobile Networks

no code implementations14 Oct 2019 Jiawen Kang, Zehui Xiong, Dusit Niyato, Yuze Zou, Yang Zhang, Mohsen Guizani

Based on this metric, a reliable worker selection scheme is proposed for federated learning tasks.

Cryptography and Security

Incentive Design for Efficient Federated Learning in Mobile Networks: A Contract Theory Approach

no code implementations16 May 2019 Jiawen Kang, Zehui Xiong, Dusit Niyato, Han Yu, Ying-Chang Liang, Dong In Kim

To strengthen data privacy and security, federated learning as an emerging machine learning technique is proposed to enable large-scale nodes, e. g., mobile devices, to distributedly train and globally share models without revealing their local data.

Federated Learning

A Survey on Consensus Mechanisms and Mining Strategy Management in Blockchain Networks

no code implementations7 May 2018 Wenbo Wang, Dinh Thai Hoang, Peizhao Hu, Zehui Xiong, Dusit Niyato, Ping Wang, Yonggang Wen, Dong In Kim

This survey is motivated by the lack of a comprehensive literature review on the development of decentralized consensus mechanisms in blockchain networks.

Cryptography and Security

Optimal Auction For Edge Computing Resource Management in Mobile Blockchain Networks: A Deep Learning Approach

no code implementations8 Nov 2017 Nguyen Cong Luong, Zehui Xiong, Ping Wang, Dusit Niyato

However, a mechanism needs to be designed for edge resource allocation to maximize the revenue for the Edge Computing Service Provider and to ensure incentive compatibility and individual rationality is still open.

Computer Science and Game Theory

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