Search Results for author: Zhu Han

Found 102 papers, 10 papers with code

Integrated Sensing and Communication Under DISCO Physical-Layer Jamming Attacks

no code implementations11 Apr 2024 Huan Huang, Hongliang Zhang, Weidong Mei, Jun Li, Yi Cai, A. Lee Swindlehurst, Zhu Han

Moreover, a theoretical analysis is conducted to quantify the impact of DISCO jamming attacks.

Harnessing the Power of AI-Generated Content for Semantic Communication

no code implementations10 Apr 2024 Yiru Wang, Wanting Yang, Zehui Xiong, Yuping Zhao, Tony Q. S. Quek, Zhu Han

Recognizing the transformative capabilities of AI-generated content (AIGC) technologies in content generation, this paper explores a pioneering approach by integrating them into SemCom to address the aforementioned challenges.

From Learning to Analytics: Improving Model Efficacy with Goal-Directed Client Selection

no code implementations30 Mar 2024 Jingwen Tong, Zhenzhen Chen, Liqun Fu, Jun Zhang, Zhu Han

To address the challenges posed by system and data heterogeneities in the FL process, we study a goal-directed client selection problem based on the model analytics framework by selecting a subset of clients for the model training.

Federated Learning

Wavenumber Domain Sparse Channel Estimation in Holographic MIMO

no code implementations17 Mar 2024 Xufeng Guo, Yuanbin Chen, Ying Wang, Zhaocheng Wang, Zhu Han

In this paper, we investigate the sparse channel estimation in holographic multiple-input multiple-output (HMIMO) systems.

Unleashing the True Power of Age-of-Information: Service Aggregation in Connected and Autonomous Vehicles

no code implementations13 Mar 2024 Anik Mallik, Dawei Chen, Kyungtae Han, Jiang Xie, Zhu Han

With an increase in AoI, incremental service aggregation issues are observed with out-of-sequence information updates, which hampers the performance of low-latency applications in CAVs.

Autonomous Vehicles

A Zero Trust Framework for Realization and Defense Against Generative AI Attacks in Power Grid

no code implementations11 Mar 2024 Md. Shirajum Munir, Sravanthi Proddatoori, Manjushree Muralidhara, Walid Saad, Zhu Han, Sachin Shetty

Understanding the potential of generative AI (GenAI)-based attacks on the power grid is a fundamental challenge that must be addressed in order to protect the power grid by realizing and validating risk in new attack vectors.

Ensemble Learning

Towards Intelligent Communications: Large Model Empowered Semantic Communications

no code implementations20 Feb 2024 Huiqiang Xie, Zhijin Qin, Xiaoming Tao, Zhu Han

First, we propose a new semantic communication architecture that seamlessly integrates large models into semantic communication through the introduction of a memory module.

Passive Beamforming For Practical RIS-Assisted Communication Systems With Non-Ideal Hardware

no code implementations15 Jan 2024 Yiming Liu, Rui Wang, Zhu Han

Reconfigurable intelligent surface (RIS) technology is a promising solution to improve the performance of existing wireless communications.

When Large Language Model Agents Meet 6G Networks: Perception, Grounding, and Alignment

no code implementations15 Jan 2024 Minrui Xu, Dusit Niyato, Jiawen Kang, Zehui Xiong, Shiwen Mao, Zhu Han, Dong In Kim, Khaled B. Letaief

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.

Language Modelling Large Language Model

ClST: A Convolutional Transformer Framework for Automatic Modulation Recognition by Knowledge Distillation

no code implementations29 Dec 2023 Dongbin Hou, Lixin Li, Wensheng Lin, Junli Liang, Zhu Han

With the rapid development of deep learning (DL) in recent years, automatic modulation recognition (AMR) with DL has achieved high accuracy.

Automatic Modulation Recognition Knowledge Distillation

Optical Integrated Sensing and Communication: Architectures, Potentials and Challenges

no code implementations21 Dec 2023 Yunfeng Wen, Fang Yang, Jian Song, Zhu Han

Integrated sensing and communication (ISAC) is viewed as a crucial component of future mobile networks and has gained much interest in both academia and industry.

Scalable AI Generative Content for Vehicular Network Semantic Communication

no code implementations23 Nov 2023 Hao Feng, Yi Yang, Zhu Han

Experimental results suggest that the proposed method surpasses the baseline in perceiving vehicles in blind spots and effectively compresses communication data.

Cross-Domain Dual-Functional OFDM Waveform Design for Accurate Sensing/Positioning

no code implementations8 Nov 2023 Fan Zhang, Tianqi Mao, Ruiqi Liu, Zhu Han, Sheng Chen, Zhaocheng Wang

For the communication-centric design, to maximize the achievable data rate, a fraction of REs are optimally allocated for communications according to prior knowledge of the communication channel.

Free Space Optical Communication for Inter-Satellite Link: Architecture, Potentials and Trends

no code implementations26 Oct 2023 Guanhua Wang, Fang Yang, Jian Song, Zhu Han

The sixth-generation (6G) network is expected to achieve global coverage based on the space-air-ground integrated network, and the latest satellite network will play an important role in it.

Scheduling

An Efficient Federated Learning Framework for Training Semantic Communication System

no code implementations20 Oct 2023 Loc X. Nguyen, Huy Q. Le, Ye Lin Tun, Pyae Sone Aung, Yan Kyaw Tun, Zhu Han, Choong Seon Hong

Semantic communication has emerged as a pillar for the next generation of communication systems due to its capabilities in alleviating data redundancy.

Federated Learning

SemantIC: Semantic Interference Cancellation Towards 6G Wireless Communications

1 code implementation19 Oct 2023 Wensheng Lin, Yuna Yan, Lixin Li, Zhu Han, Tad Matsumoto

This letter proposes a novel anti-interference technique, semantic interference cancellation (SemantIC), for enhancing information quality towards the sixth-generation (6G) wireless networks.

Semantic-Forward Relaying: A Novel Framework Towards 6G Cooperative Communications

1 code implementation12 Oct 2023 Wensheng Lin, Yuna Yan, Lixin Li, Zhu Han, Tad Matsumoto

This letter proposes a novel relaying framework, semantic-forward (SF), for cooperative communications towards the sixth-generation (6G) wireless networks.

Semi-Federated Learning: Convergence Analysis and Optimization of A Hybrid Learning Framework

no code implementations4 Oct 2023 Jingheng Zheng, Wanli Ni, Hui Tian, Deniz Gunduz, Tony Q. S. Quek, Zhu Han

To tackle this issue, we propose a semi-federated learning (SemiFL) paradigm to leverage the computing capabilities of both the BS and devices for a hybrid implementation of centralized learning (CL) and FL.

Federated Learning

DISCO Might Not Be Funky: Random Intelligent Reflective Surface Configurations That Attack

no code implementations1 Oct 2023 Huan Huang, Lipeng Dai, Hongliang Zhang, Chongfu Zhang, Zhongxing Tian, Yi Cai, A. Lee Swindlehurst, Zhu Han

Moreover, we outline future research directions and challenges for the DIRS-based FPJ and its anti-jamming precoding to stimulate this line of research and pave the way for practical applications.

Federated Learning in Intelligent Transportation Systems: Recent Applications and Open Problems

no code implementations20 Sep 2023 Shiying Zhang, Jun Li, Long Shi, Ming Ding, Dinh C. Nguyen, Wuzheng Tan, Jian Weng, Zhu Han

Intelligent transportation systems (ITSs) have been fueled by the rapid development of communication technologies, sensor technologies, and the Internet of Things (IoT).

Federated Learning Object Recognition

Channel Reciprocity Attacks Using Intelligent Surfaces with Non-Diagonal Phase Shifts

no code implementations20 Sep 2023 Haoyu Wang, Zhu Han, A. Lee Swindlehurst

While reconfigurable intelligent surface (RIS) technology has been shown to provide numerous benefits to wireless systems, in the hands of an adversary such technology can also be used to disrupt communication links.

A Generalized Delay and Backlog Analysis for Multiplexing URLLC and eMBB: Reconfigurable Intelligent Surfaces or Decode-and-Forward?

1 code implementation IEEE Transactions on Wireless Communications 2023 Haoran Peng, Ching-Chieh Hsia, Zhu Han, and Li-Chun Wang

By creating multipath backscatter links and amplify signal strength, reconfigurable intelligent surfaces (RIS) and decode-and-forward (DF) relaying are shown to degrade the latency of the ultrareliable low-latency communications (URLLCs) and enhanced mobile broadband (eMBB) multiplexing system.

Scheduling

Mean Field Game-based Waveform Precoding Design for Mobile Crowd Integrated Sensing, Communication, and Computation Systems

no code implementations6 Sep 2023 Dezhi Wang, Chongwen Huang, Jiguang He, Xiaoming Chen, Wei Wang, Zhaoyang Zhang, Zhu Han, Mérouane Debbah

In this paper, we consider the environment sensing problem in the large-scale mobile crowd ISCC systems and propose an efficient waveform precoding design algorithm based on the mean field game~(MFG).

Anti-Jamming Precoding Against Disco Intelligent Reflecting Surfaces Based Fully-Passive Jamming Attacks

no code implementations30 Aug 2023 Huan Huang, Lipeng Dai, Hongliang Zhang, Zhongxing Tian, Yi Cai, Chongfu Zhang, A. Lee Swindlehurst, Zhu Han

Numerical results are also presented to evaluate the effectiveness of the proposed anti-jamming precoder against the DIRS-based FPJs and the feasibility of the designed data frame used by the legitimate AP to estimate the statistical characteristics.

RIS-assisted High-Speed Railway Integrated Sensing and Communication System

no code implementations19 Aug 2023 Panpan Li, Yong Niu, Hao Wu, Zhu Han, Guiqi Sun, Ning Wang, Zhangdui Zhong, Bo Ai

One technology that has the potential to improve wireless communications in years to come is integrated sensing and communication (ISAC).

A New Heterogeneous Hybrid Massive MIMO Receiver with An Intrinsic Ability of Removing Phase Ambiguity of DOA Estimation via Machine Learning

no code implementations16 Aug 2023 Feng Shu, Baihua Shi, YiWen Chen, Jiatong Bai, YiFan Li, Tingting Liu, Zhu Han

To address this problem, a new heterogeneous sub-connected hybrid analog and digital (HAD) MIMO structure is proposed with an intrinsic ability of removing phase ambiguity and a corresponding new framework is developed to implement a rapid high-precision DOA estimation using only single time-slot.

Clustering

An Anti-Jamming Strategy for Disco Intelligent Reflecting Surfaces Based Fully-Passive Jamming Attacks

no code implementations7 Jul 2023 Huan Huang, Hongliang Zhang, Yi Cai, A. Lee Swindlehurst, Zhu Han

Emerging intelligent reflecting surfaces (IRSs) significantly improve system performance, while also pose a huge risk for physical layer security.

Dynamic UAV Swarm Collaboration for Multi-Targets Tracking under Malicious Jamming: Joint Power, Path and Target Association Optimization

no code implementations28 Jun 2023 Lanhua Xiang, Fengyu Wang, Wenjun Xu, Tiankui Zhang, Miao Pan, Zhu Han

First, a cluster-evolutionary target association (CETA) algorithm is proposed, which involves dividing the UAV swarm into the multiple sub-swarms and individually matching these sub-swarms to targets.

Physical-layer Adversarial Robustness for Deep Learning-based Semantic Communications

no code implementations12 May 2023 Guoshun Nan, Zhichun Li, Jinli Zhai, Qimei Cui, Gong Chen, Xin Du, Xuefei Zhang, Xiaofeng Tao, Zhu Han, Tony Q. S. Quek

We argue that central to the success of ESC is the robust interpretation of conveyed semantics at the receiver side, especially for security-critical applications such as automatic driving and smart healthcare.

Adversarial Robustness

Location Tracking for Reconfigurable Intelligent Surfaces Aided Vehicle Platoons: Diverse Sparsities Inspired Approaches

no code implementations7 May 2023 Yuanbin Chen, Ying Wang, Xufeng Guo, Zhu Han, Ping Zhang

In this paper, we investigate the employment of reconfigurable intelligent surfaces (RISs) into vehicle platoons, functioning in tandem with a base station (BS) in support of the high-precision location tracking.

Bayesian Inference Philosophy

Robust Trajectory and Offloading for Energy-Efficient UAV Edge Computing in Industrial Internet of Things

no code implementations8 Mar 2023 Xiao Tang, Hongrui Zhang, Ruonan Zhang, Deyun Zhou, Yan Zhang, Zhu Han

In this paper, we employ an unmanned aerial vehicle (UAV) as an edge server to assist IIoT data processing, while considering the practical issue of UAV jittering.

Edge-computing

Robust Secrecy via Aerial Reflection and Jamming: Joint Optimization of Deployment and Transmission

no code implementations28 Feb 2023 Xiao Tang, Hongliang He, Limeng Dong, Lixin Li, Qinghe Du, Zhu Han

The security gain with aerial reflection and jamming is further improved with the optimized deployment of the aerial platform.

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

1 code implementation16 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

Computation and Privacy Protection for Satellite-Ground Digital Twin Networks

no code implementations16 Feb 2023 Yongkang Gong, Haipeng Yao Xiaonan Liu, Mehdi Bennis, Arumugam Nallanathan, Zhu Han

Satellite-ground integrated digital twin networks (SGIDTNs) are regarded as innovative network architectures for reducing network congestion, enabling nearly-instant data mapping from the physical world to digital systems, and offering ubiquitous intelligence services to terrestrial users.

Scheduling

Disco Intelligent Reflecting Surfaces: Active Channel Aging for Fully-Passive Jamming Attacks

no code implementations1 Feb 2023 Huan Huang, Ying Zhang, Hongliang Zhang, Yi Cai, A. Lee Swindlehurst, Zhu Han

A theoretical analysis of the proposed DIRS-based FPJ that provides an evaluation of the DIRS-based jamming attacks is derived.

Quantization

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

Multiple-Antenna Aided Aeronautical Communications in Air-Ground Integrated Networks: Channel Estimation, Reliable Transmission, and Multiple Access

no code implementations15 Jan 2023 Jingjing Zhao, YanBo Zhu, Kaiquan Cai, Zhen Gao, Zhu Han, Lajos Hanzo

To provide seamless coverage during all flight phases, aeronautical communications systems (ACS) have to integrate space-based, air-based, as well as ground-based platforms to formulate aviation-oriented space-air-ground integrated networks (SAGINs).

Management

Beyond 5G Networks: Integration of Communication, Computing, Caching, and Control

no code implementations26 Dec 2022 Musbahu Mohammed Adam, Liqiang Zhao, Kezhi Wang, Zhu Han

In recent years, the exponential proliferation of smart devices with their intelligent applications poses severe challenges on conventional cellular networks.

Gradient and Channel Aware Dynamic Scheduling for Over-the-Air Computation in Federated Edge Learning Systems

no code implementations1 Dec 2022 Jun Du, Bingqing Jiang, Chunxiao Jiang, Yuanming Shi, Zhu Han

To further improve the efficiency of wireless data aggregation and model learning, over-the-air computation (AirComp) is emerging as a promising solution by using the superposition characteristics of wireless channels.

Federated Learning Privacy Preserving +1

Less Data, More Knowledge: Building Next Generation Semantic Communication Networks

no code implementations25 Nov 2022 Christina Chaccour, Walid Saad, Merouane Debbah, Zhu Han, H. Vincent Poor

In this tutorial, we present the first rigorous vision of a scalable end-to-end semantic communication network that is founded on novel concepts from artificial intelligence (AI), causal reasoning, and communication theory.

Novel Concepts Representation Learning

3-D Positioning and Resource Allocation for Multi-UAV Base Stations Under Blockage-Aware Channel Model

no code implementations23 Nov 2022 Pengfei Yi, Lipeng Zhu, Zhenyu Xiao, Rui Zhang, Zhu Han, Xiang-Gen Xia

Based on the proposed channel model, we formulate the joint optimization problem of UAV three-dimensional (3-D) positioning and resource allocation, by power allocation, user association, and subcarrier allocation, to maximize the minimum achievable rate among users.

Identifying Operation Equilibrium in Integrated Electricity, Natural Gas, and Carbon-Emission Markets

no code implementations18 Oct 2022 Yijie Yang, Jian Shi, Dan Wang, Chenye Wu, Zhu Han

Carbon emission markets can play a significant role in this transition by putting a price on carbon and giving electricity producers an incentive to reduce their emissions.

Deep Decarbonization of Multi-Energy Systems: A Carbon-Oriented Framework with Cross Disciplinary Technologies

no code implementations17 Oct 2022 Jian Shi, Dan Wang, Chenye Wu, Zhu Han

The retirement of unabated coal power plants, the plummeting cost of renewable energy technologies, along with more aggressive public policies and regulatory reforms, are occurring at an unprecedented speed to decarbonize the power and energy systems towards the 2030 and 2050 climate goals.

Near Space Communications (NS-COM): A New Regime in Space-Air-Ground Integrated Network (SAGIN)

no code implementations25 Jul 2022 Zhenyu Xiao, Tianqi Mao, Zhu Han, Xiang-Gen Xia

Precipitated by the technological innovations of the near-space platform stations (NSPS), the near space communication (NS-COM) network has emerged as an indispensable part of the next-generation space-air-ground integrated network (SAGIN) that facilitates ubiquitous coverage and broadband data transfer.

Terahertz-Band Near-Space Communications: From a Physical-Layer Perspective

no code implementations25 Jul 2022 Tianqi Mao, Leyi Zhang, Zhenyu Xiao, Zhu Han, Xiang-Gen Xia

Facilitated by rapid technological development of the near-space platform stations (NSPS), near-space communication (NS-COM) is envisioned to play a pivotal role in the space-air-ground integrated network for sixth-generation (6G) communications and beyond.

LEO Satellite Access Network (LEO-SAN) Towards 6G: Challenges and Approaches

1 code implementation25 Jul 2022 Zhenyu Xiao, Junyi Yang, Tianqi Mao, Chong Xu, Rui Zhang, Zhu Han, Xiang-Gen Xia

With the rapid development of satellite communication technologies, the space-based access network has been envisioned as a promising complementary part of the future 6G network.

Management

Data-and-Knowledge Dual-Driven Automatic Modulation Recognition for Wireless Communication Networks

no code implementations30 Jun 2022 Rui Ding, Hao Zhang, Fuhui Zhou, Qihui Wu, Zhu Han

In order to tackle these problems, a novel data-and-knowledge dual-driven automatic modulation classification scheme based on radio frequency machine learning is proposed by exploiting the attribute features of different modulations.

Attribute Automatic Modulation Recognition +1

Meta-material Sensor Based Internet of Things: Design, Optimization, and Implementation

no code implementations26 Jun 2022 Jingzhi Hu, Hongliang Zhang, Boya Di, Zhu Han, H. Vincent Poor, Lingyang Song

However, to maximize the sensing accuracy, the structures of meta-IoT sensors need to be optimized considering their joint influence on sensing and transmission, which is challenging due to the high computational complexity in evaluating the influence, especially given a large number of sensors.

Mixture GAN For Modulation Classification Resiliency Against Adversarial Attacks

no code implementations29 May 2022 Eyad Shtaiwi, Ahmed El Ouadrhiri, Majid Moradikia, Salma Sultana, Ahmed Abdelhadi, Zhu Han

In this paper, we propose a novel generative adversarial network (GAN)-based countermeasure approach to safeguard the DNN-based AMC systems against adversarial attack examples.

Adversarial Attack Classification +2

LEAF + AIO: Edge-Assisted Energy-Aware Object Detection for Mobile Augmented Reality

no code implementations27 May 2022 Haoxin Wang, BaekGyu Kim, Jiang Xie, Zhu Han

In this paper, we design an edge-based energy-aware MAR system that enables MAR devices to dynamically change their configurations, such as CPU frequency, computation model size, and image offloading frequency based on user preferences, camera sampling rates, and available radio resources.

object-detection Object Detection

Tensor Decompositions for Hyperspectral Data Processing in Remote Sensing: A Comprehensive Review

no code implementations13 May 2022 Minghua Wang, Danfeng Hong, Zhu Han, Jiaxin Li, Jing Yao, Lianru Gao, Bing Zhang, Jocelyn Chanussot

Owing to the rapid development of sensor technology, hyperspectral (HS) remote sensing (RS) imaging has provided a significant amount of spatial and spectral information for the observation and analysis of the Earth's surface at a distance of data acquisition devices, such as aircraft, spacecraft, and satellite.

Anomaly Detection Super-Resolution +1

LEOPARD: Parallel Optimal Deep Echo State Network Prediction Improves Service Coverage for UAV-Assisted Outdoor Hotspots

1 code implementation IEEE Transactions on Cognitive Communications and Networking 2022 Haoran Peng, Ang-Hsun Tsai, Li-Chun Wang, Zhu Han

Unmanned aerial vehicle (UAV) base stations (BSs) can help meet the dynamic traffic demand of flash mobile crowds, but user movements also pose a significant challenge on fast-tracking for avoiding service interruption.

Bayesian Optimization

MetaRadar: Multi-target Detection for Reconfigurable Intelligent Surface Aided Radar Systems

no code implementations25 Feb 2022 Haobo Zhang, Hongliang Zhang, Boya Di, Kaigui Bian, Zhu Han, Lingyang Song

To address this issue, we propose to use the reconfigurable intelligent surface (RIS) to improve the detection accuracy of radar systems due to its capability to customize channel conditions by adjusting its phase shifts, which is referred to as MetaRadar.

Artificial Intelligence for the Metaverse: A Survey

no code implementations15 Feb 2022 Thien Huynh-The, Quoc-Viet Pham, Xuan-Qui Pham, Thanh Thi Nguyen, Zhu Han, Dong-Seong Kim

Many virtual environments with thousands of services and applications, from social networks to virtual gaming worlds, have been developed with immersive experience and digital transformation, but most are incoherent instead of being integrated into a platform.

Deep Reinforcement Learning Assisted Federated Learning Algorithm for Data Management of IIoT

no code implementations3 Feb 2022 Peiying Zhang, Chao Wang, Chunxiao Jiang, Zhu Han

Therefore, we propose a FL algorithm assisted by DRL, which can take into account the privacy and efficiency of data training of IIoT equipment.

Federated Learning Management +3

An Adaptive Device-Edge Co-Inference Framework Based on Soft Actor-Critic

no code implementations9 Jan 2022 Tao Niu, Yinglei Teng, Zhu Han, Panpan Zou

Recently, the applications of deep neural network (DNN) have been very prominent in many fields such as computer vision (CV) and natural language processing (NLP) due to its superior feature extraction performance.

Quantization

Reconfigurable Holographic Surfaces for Future Wireless Communications

no code implementations13 Dec 2021 Ruoqi Deng, Boya Di, Hongliang Zhang, Dusit Niyato, Zhu Han, H. Vincent Poor, Lingyang Song

Future wireless communications look forward to constructing a ubiquitous intelligent information network with high data rates through cost-efficient devices.

Joint 3-D Positioning and Power Allocation for UAV Relay Aided by Geographic Information

no code implementations12 Oct 2021 Pengfei Yi, Liang Zhu, Lipeng Zhu, Zhenyu Xiao, Zhu Han, Xiang-Gen Xia

To improve communication capacity, we first model the blockage effect caused by buildings according to the three-dimensional (3-D) geographic information.

MetaSketch: Wireless Semantic Segmentation by Metamaterial Surfaces

no code implementations14 Aug 2021 Jingzhi Hu, Hongliang Zhang, Kaigui Bian, Zhu Han, H. Vincent Poor, Lingyang Song

Semantic segmentation is a process of partitioning an image into multiple segments for recognizing humans and objects, which can be widely applied in scenarios such as healthcare and safety monitoring.

Compressive Sensing Object Recognition +1

SpectralFormer: Rethinking Hyperspectral Image Classification with Transformers

2 code implementations7 Jul 2021 Danfeng Hong, Zhu Han, Jing Yao, Lianru Gao, Bing Zhang, Antonio Plaza, Jocelyn Chanussot

Hyperspectral (HS) images are characterized by approximately contiguous spectral information, enabling the fine identification of materials by capturing subtle spectral discrepancies.

Classification Hyperspectral Image Classification

On the Impact of Oscillator Phase Noise in an IRS-assisted MISO TDD System

no code implementations6 Jul 2021 Chu Li, Aydin Sezgin, Zhu Han

In this work, we study the impact of the multiplicative phase noise in an IRS-assisted system.

Adaptive Stochastic ADMM for Decentralized Reinforcement Learning in Edge Industrial IoT

no code implementations30 Jun 2021 Wanlu Lei, Yu Ye, Ming Xiao, Mikael Skoglund, Zhu Han

Alternating direction method of multipliers (ADMM) has a structure that allows for decentralized implementation, and has shown faster convergence than gradient descent based methods.

Decision Making Edge-computing +2

Low-Latency Federated Learning over Wireless Channels with Differential Privacy

no code implementations20 Jun 2021 Kang Wei, Jun Li, Chuan Ma, Ming Ding, Cailian Chen, Shi Jin, Zhu Han, H. Vincent Poor

Then, we convert the MAMAB to a max-min bipartite matching problem at each communication round, by estimating rewards with the upper confidence bound (UCB) approach.

Federated Learning

Minimizing Delay in Network Function Visualization with Quantum Computing

no code implementations20 Jun 2021 Wenlu Xuan, Zhongqi Zhao, Lei Fan, Zhu Han

There are vast service chains in NFV to meet users' requests, which are composed of a sequence of network functions.

Scheduling

Spatial Equalization Before Reception: Reconfigurable Intelligent Surfaces for Multi-path Mitigation

no code implementations8 Mar 2021 Hongliang Zhang, Lingyang Song, Zhu Han, H. Vincent Poor

Reconfigurable intelligent surfaces (RISs), which enable tunable anomalous reflection, have appeared as a promising method to enhance wireless systems.

Information Theory Information Theory

Digital-Twin-Enabled 6G: Vision, Architectural Trends, and Future Directions

no code implementations24 Feb 2021 Latif U. Khan, Walid Saad, Dusit Niyato, Zhu Han, Choong Seon Hong

Therefore, enabling IoE applications over 6G requires a new framework that can be used to manage, operate, and optimize the 6G wireless system and its underlying IoE services.

Edge-computing Networking and Internet Architecture

Coalition Game Based Full-duplex Popular Content Distribution in mmWave Vehicular Networks

no code implementations29 Jan 2021 Yibing Wang, Hao Wu, Yong Niu, Zhu Han, Bo Ai, Zhangdui Zhong

We evaluate the proposed scheme by extensive simulations in mmWave vehicular networks.

Fairness Information Theory Networking and Internet Architecture Information Theory

Blockchain Assisted Decentralized Federated Learning (BLADE-FL): Performance Analysis and Resource Allocation

no code implementations18 Jan 2021 Jun Li, Yumeng Shao, Kang Wei, Ming Ding, Chuan Ma, Long Shi, Zhu Han, H. Vincent Poor

Focusing on this problem, we explore the impact of lazy clients on the learning performance of BLADE-FL, and characterize the relationship among the optimal K, the learning parameters, and the proportion of lazy clients.

Federated Learning

To Talk or to Work: Flexible Communication Compression for Energy Efficient Federated Learning over Heterogeneous Mobile Edge Devices

no code implementations22 Dec 2020 Liang Li, Dian Shi, Ronghui Hou, Hui Li, Miao Pan, Zhu Han

Recent advances in machine learning, wireless communication, and mobile hardware technologies promisingly enable federated learning (FL) over massive mobile edge devices, which opens new horizons for numerous intelligent mobile applications.

Federated Learning

Blockchain Assisted Decentralized Federated Learning (BLADE-FL) with Lazy Clients

no code implementations2 Dec 2020 Jun Li, Yumeng Shao, Ming Ding, Chuan Ma, Kang Wei, Zhu Han, H. Vincent Poor

The proposed BLADE-FL has a good performance in terms of privacy preservation, tamper resistance, and effective cooperation of learning.

Federated Learning

Edge-assisted Democratized Learning Towards Federated Analytics

no code implementations1 Dec 2020 Shashi Raj Pandey, Minh N. H. Nguyen, Tri Nguyen Dang, Nguyen H. Tran, Kyi Thar, Zhu Han, Choong Seon Hong

Therefore, we need to design a robust learning mechanism than the FL that (i) unleashes a viable infrastructure for FA and (ii) trains learning models with better generalization capability.

Distributed Computing Edge-computing +1

Energy Drain of the Object Detection Processing Pipeline for Mobile Devices: Analysis and Implications

no code implementations26 Nov 2020 Haoxin Wang, BaekGyu Kim, Jiang Xie, Zhu Han

In order to accurately measure the energy consumption on the smartphone and obtain the breakdown of energy consumed by each phase of the object detection processing pipeline, we propose a new measurement strategy.

Object object-detection +1

MetaSensing: Intelligent Metasurface Assisted RF 3D Sensing by Deep Reinforcement Learning

no code implementations25 Nov 2020 Jingzhi Hu, Hongliang Zhang, Kaigui Bian, Marco Di Renzo, Zhu Han, Lingyang Song

To tackle this challenge, we formulate an optimization problem for minimizing the cross-entropy loss of the sensing outcome, and propose a deep reinforcement learning algorithm to jointly compute the optimal beamformer patterns and the mapping of the received signals.

reinforcement-learning Reinforcement Learning (RL)

Toward Multiple Federated Learning Services Resource Sharing in Mobile Edge Networks

1 code implementation25 Nov 2020 Minh N. H. Nguyen, Nguyen H. Tran, Yan Kyaw Tun, Zhu Han, Choong Seon Hong

Federated Learning is a new learning scheme for collaborative training a shared prediction model while keeping data locally on participating devices.

Edge-computing Federated Learning

MetaLocalization: Reconfigurable Intelligent Surface Aided Multi-user Wireless Indoor Localization

no code implementations18 Nov 2020 Haobo Zhang, Hongliang Zhang, Boya Di, Kaigui Bian, Zhu Han, Lingyang Song

As the RIS is able to customize the radio channels by adjusting the phase shifts of the signals reflected at the surface, the localization accuracy in the RIS aided scheme can be improved by choosing the proper phase shifts with significant differences of RSS values among adjacent locations.

Indoor Localization

Intelligent Omni-Surface: Ubiquitous Wireless Transmission by Reflective-Transmissive Metasurface

no code implementations2 Nov 2020 Shuhang Zhang, Hongliang Zhang, Boya Di, Yunhua Tan, Marco Di Renzo, Zhu Han, H. Vincent Poor, Lingyang Song

Intelligent reflecting surface (IRS), which is capable to adjust propagation conditions by controlling phase shifts of the reflected waves that impinge on the surface, has been widely analyzed for enhancing the performance of wireless systems.

Federated Learning for Internet of Things: Recent Advances, Taxonomy, and Open Challenges

no code implementations28 Sep 2020 Latif U. Khan, Walid Saad, Zhu Han, Ekram Hossain, Choong Seon Hong

However, given the presence of massively distributed and private datasets, it is challenging to use classical centralized learning algorithms in the IoT.

Networking and Internet Architecture

Architectural Design Alternatives based on Cloud/Edge/Fog Computing for Connected Vehicles

no code implementations26 Sep 2020 Haoxin Wang, Tingting Liu, BaekGyu Kim, Chung-Wei Lin, Shinichi Shiraishi, Jiang Xie, Zhu Han

These requirements ask for a well-designed computing architecture to support the Quality-of-Service (QoS) of CV applications.

Networking and Internet Architecture

When Federated Learning Meets Blockchain: A New Distributed Learning Paradigm

no code implementations20 Sep 2020 Chuan Ma, Jun Li, Ming Ding, Long Shi, Taotao Wang, Zhu Han, H. Vincent Poor

Motivated by the explosive computing capabilities at end user equipments, as well as the growing privacy concerns over sharing sensitive raw data, a new machine learning paradigm, named federated learning (FL) has emerged.

Networking and Internet Architecture

Sense-Store-Send: Trajectory Optimization for a Buffer-aided Internet of UAVs

no code implementations15 Sep 2020 Yujie Jin, Hongliang Zhang, Shuhang Zhang, Zhu Han, Lingyang Song

To minimize the overall completion time for all the sensing tasks, we formulate a joint trajectory, sensing location, and sensing time optimization problem.

On Spatial Multiplexing Using Reconfigurable Intelligent Surfaces

no code implementations15 Sep 2020 Mohamed A. ElMossallamy, Hongliang Zhang, Radwa Sultan, Karim G. Seddik, Lingyang Song, Geoffery Ye Li, Zhu Han

We consider an uplink multi-user scenario and investigate the use of reconfigurable intelligent surfaces (RIS) to optimize spatial multiplexing performance when a linear receiver is used.

Beyond Intelligent Reflecting Surfaces: Reflective-Transmissive Metasurface Aided Communications for Full-dimensional Coverage Extension

no code implementations15 Sep 2020 Shuhang Zhang, Hongliang Zhang, Boya Di, Yunhua Tan, Zhu Han, Lingyang Song

In this paper, we study an intelligent omni-surface (IOS)-assisted downlink communication system, where the link quality of a mobile user (MU) can be improved with a proper IOS phase shift design.

Signal Processing

Dispersed Federated Learning: Vision, Taxonomy, and Future Directions

no code implementations12 Aug 2020 Latif U. Khan, Walid Saad, Zhu Han, Choong Seon Hong

However, federated learning still has privacy concerns due to sensitive information inferring capability of the aggregation server using end-devices local learning models.

Distributed, Parallel, and Cluster Computing

MetaRadar: Indoor Localization by Reconfigurable Metamaterials

no code implementations6 Aug 2020 Haobo Zhang, Jingzhi Hu, Hongliang Zhang, Boya Di, Kaigui Bian, Zhu Han, Lingyang Song

However, in MetaRadar, it is challenging to build radio maps for all the radio environments generated by metamaterial units and select suitable maps from all the possible maps to realize a high accuracy localization.

Indoor Localization

Adaptive Compressive Sampling for Mid-infrared Spectroscopic Imaging

no code implementations2 Aug 2020 Mahsa Lotfollahi, Nguyen Tran, Sebastian Berisha, Chalapathi Gajjela, Zhu Han, David Mayerich, Rohith Reddy

Minfrared spectroscopic imaging (MIRSI) is an emerging class of label-free, biochemically quantitative technologies targeting digital histopathology.

Deep Learning Techniques for Future Intelligent Cross-Media Retrieval

no code implementations21 Jul 2020 Sadaqat ur Rehman, Muhammad Waqas, Shanshan Tu, Anis Koubaa, Obaid ur Rehman, Jawad Ahmad, Muhammad Hanif, Zhu Han

With the advancement in technology and the expansion of broadcasting, cross-media retrieval has gained much attention.

Retrieval

Towards Ubiquitous Positioning by Leveraging Reconfigurable Intelligent Surface

no code implementations10 Jul 2020 Haobo Zhang, Hongliang Zhang, Boya Di, Kaigui Bian, Zhu Han, Lingyang Song

The received signal strength (RSS) based technique is widely utilized for ubiquitous positioning due to its advantage of simple implementability.

Codebook-Based Beam Tracking for Conformal ArrayEnabled UAV MmWave Networks

no code implementations28 May 2020 Jinglin Zhang, Wenjun Xu, Hui Gao, Miao Pan, Zhu Han, Ping Zhang

Aiming to address the beam tracking difficulties, we propose to integrate the conformal array (CA) with the surface of each UAV, which enables the full spatial coverage and the agile beam tracking in highly dynamic UAV mmWave networks.

Reconfigurable Intelligent Surfaces for Wireless Communications: Principles, Challenges, and Opportunities

no code implementations2 May 2020 Mohamed A. ElMossallamy, Hongliang Zhang, Lingyang Song, Karim G. Seddik, Zhu Han, Geoffrey Ye Li

Recently there has been a flurry of research on the use of reconfigurable intelligent surfaces (RIS) in wireless networks to create smart radio environments.

Decentralized Learning for Channel Allocation in IoT Networks over Unlicensed Bandwidth as a Contextual Multi-player Multi-armed Bandit Game

1 code implementation30 Mar 2020 Wenbo Wang, Amir Leshem, Dusit Niyato, Zhu Han

We study a decentralized channel allocation problem in an ad-hoc Internet of Things network underlaying on the spectrum licensed to a primary cellular network.

Hyperspectral-Multispectral Image Fusion with Weighted LASSO

no code implementations15 Mar 2020 Nguyen Tran, Rupali Mankar, David Mayerich, Zhu Han

Hyperspectral imaging provides superior material specificity, while multispectral images are faster to collect at greater fidelity.

Astronomy Specificity +1

Data Freshness and Energy-Efficient UAV Navigation Optimization: A Deep Reinforcement Learning Approach

no code implementations21 Feb 2020 Sarder Fakhrul Abedin, Md. Shirajum Munir, Nguyen H. Tran, Zhu Han, Choong Seon Hong

First, we formulate an energy-efficient trajectory optimization problem in which the objective is to maximize the energy efficiency by optimizing the UAV-BS trajectory policy.

reinforcement-learning Reinforcement Learning (RL)

Risk-Aware Energy Scheduling for Edge Computing with Microgrid: A Multi-Agent Deep Reinforcement Learning Approach

no code implementations21 Feb 2020 Md. Shirajum Munir, Sarder Fakhrul Abedin, Nguyen H. Tran, Zhu Han, Eui-Nam Huh, Choong Seon Hong

First, we formulate an optimization problem considering the conditional value-at-risk (CVaR) measurement for both energy consumption and generation, where the objective is to minimize the expected residual of scheduled energy for the MEC networks and we show this problem is an NP-hard problem.

Edge-computing Scheduling

Optimal Pricing of Internet of Things: A Machine Learning Approach

no code implementations14 Feb 2020 Mohammad Abu Alsheikh, Dinh Thai Hoang, Dusit Niyato, Derek Leong, Ping Wang, Zhu Han

For service bundles, the subscription fee and data sizes of the grouped IoT services are optimized to maximize the total profit of cooperative service providers.

BIG-bench Machine Learning

Federated Learning for Edge Networks: Resource Optimization and Incentive Mechanism

no code implementations6 Nov 2019 Latif U. Khan, Nguyen H. Tran, Shashi Raj Pandey, Walid Saad, Zhu Han, Minh N. H. Nguyen, Choong Seon Hong

IoT devices with intelligence require the use of effective machine learning paradigms.

Distributed, Parallel, and Cluster Computing

A Predictive On-Demand Placement of UAV Base Stations Using Echo State Network

no code implementations25 Sep 2019 Haoran Peng, Chao Chen, Chuan-Chi Lai, Li-Chun Wang, Zhu Han

In this paper, we propose a system framework consisting of UEs clustering, UAV-BS placement, UEs trajectories prediction, and UAV-BS reposition matching scheme, to serve the UEs seamlessly as well as minimize the energy cost of UAV-BSs' reposition trajectories.

Clustering

A Deep Spatio-Temporal Fuzzy Neural Network for Passenger Demand Prediction

no code implementations13 May 2019 Xiaoyuan Liang, Guiling Wang, Martin Renqiang Min, Yi Qi, Zhu Han

In spite of its importance, passenger demand prediction is a highly challenging problem, because the demand is simultaneously influenced by the complex interactions among many spatial and temporal factors and other external factors such as weather.

Regional Robust Secure Precise Wireless Transmission Design for Multi-user UAV Broadcasting System

no code implementations9 Apr 2019 Tong Shen, Tingting Liu, Yan Lin, Yongpeng Wu, Feng Shu, Zhu Han

Proposed regional robust schemes are designed for optimizing the secrecy performance in the whole error region around the estimated location.

Deep Reinforcement Learning for Traffic Light Control in Vehicular Networks

3 code implementations29 Mar 2018 Xiaoyuan Liang, Xunsheng Du, Guiling Wang, Zhu Han

In terms of how to dynamically adjust traffic signals' duration, existing works either split the traffic signal into equal duration or extract limited traffic information from the real data.

Q-Learning reinforcement-learning +1

Mobile Big Data Analytics Using Deep Learning and Apache Spark

no code implementations23 Feb 2016 Mohammad Abu Alsheikh, Dusit Niyato, Shaowei Lin, Hwee-Pink Tan, Zhu Han

The proliferation of mobile devices, such as smartphones and Internet of Things (IoT) gadgets, results in the recent mobile big data (MBD) era.

Activity Recognition

Non-parametric Bayesian Learning with Deep Learning Structure and Its Applications in Wireless Networks

no code implementations16 Oct 2014 Erte Pan, Zhu Han

In this paper, we present an infinite hierarchical non-parametric Bayesian model to extract the hidden factors over observed data, where the number of hidden factors for each layer is unknown and can be potentially infinite.

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