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All Outputs (37)

Machine Learning for Smart Healthcare Management Using IoT (2023)
Book Chapter
Yigit, Y., Duran, K., Moradpoor, N., Maglaras, L., Van Huynh, N., & Canberk, B. (in press). Machine Learning for Smart Healthcare Management Using IoT. In IoT and ML for Information Management: A Smart Healthcare Perspective. Springer

The convergence of Machine Learning (ML) and the Internet of Things (IoT) has brought about a paradigm shift in healthcare, ushering in a new era of intelligent healthcare management. This powerful amalgamation is driving transformative changes acros... Read More about Machine Learning for Smart Healthcare Management Using IoT.

Distributed-Training-and-Execution Multi-Agent Reinforcement Learning for Power Control in HetNet (2023)
Journal Article
Xu, K., Huynh, N. V., & Li, G. Y. (2023). Distributed-Training-and-Execution Multi-Agent Reinforcement Learning for Power Control in HetNet. IEEE Transactions on Communications, 71(10), 5893 - 5903. https://doi.org/10.1109/tcomm.2023.3300331

In heterogeneous networks (HetNets), the overlap of small cells and the macro cell causes severe cross-tier interference. Although there exist some approaches to address this problem, they usually require global channel state information, which is ha... Read More about Distributed-Training-and-Execution Multi-Agent Reinforcement Learning for Power Control in HetNet.

Defeating Eavesdroppers with Ambient Backscatter Communications (2023)
Conference Proceeding
Huynh, N. V., Quang Hieu, N., Chu, N. H., Nguyen, D. N., Hoang, D. T., & Dutkiewicz, E. (2023). Defeating Eavesdroppers with Ambient Backscatter Communications. In 2023 IEEE Wireless Communications and Networking Conference (WCNC) Proceedings. https://doi.org/10.1109/wcnc55385.2023.10118774

Unlike conventional anti-eavesdropping methods that always require additional energy or computing resources (e.g., in friendly jamming and cryptography-based solutions), this work proposes a novel anti-eavesdropping solution that comes with mostly no... Read More about Defeating Eavesdroppers with Ambient Backscatter Communications.

Transfer Learning for Signal Detection in Wireless Networks (2022)
Journal Article
Van Huynh, N., & Li, G. Y. (2022). Transfer Learning for Signal Detection in Wireless Networks. IEEE Wireless Communications Letters, 11(11), 2325-2329. https://doi.org/10.1109/lwc.2022.3202117

The last decade has witnessed the rapid growth of deep learning (DL) applications in wireless communications, especially for channel estimation and signal detection. However, conventional DL techniques are usually trained for a specific scenario. The... Read More about Transfer Learning for Signal Detection in Wireless Networks.

Transfer Learning for Wireless Networks: A Comprehensive Survey (2022)
Journal Article
Nguyen, C. T., Van Huynh, N., Chu, N. H., Saputra, Y. M., Hoang, D. T., Nguyen, D. N., …Hwang, W. (2022). Transfer Learning for Wireless Networks: A Comprehensive Survey. Proceedings of the IEEE, 110(8), 1073-1115. https://doi.org/10.1109/jproc.2022.3175942

With outstanding features, machine learning (ML) has become the backbone of numerous applications in wireless networks. However, the conventional ML approaches face many challenges in practical implementation, such as the lack of labeled data, the co... Read More about Transfer Learning for Wireless Networks: A Comprehensive Survey.

Joint Speed Control and Energy Replenishment Optimization for UAV-Assisted IoT Data Collection With Deep Reinforcement Transfer Learning (2022)
Journal Article
Chu, N. H., Hoang, D. T., Nguyen, D. N., Van Huynh, N., & Dutkiewicz, E. (2023). Joint Speed Control and Energy Replenishment Optimization for UAV-Assisted IoT Data Collection With Deep Reinforcement Transfer Learning. IEEE Internet of Things, 10(7), 5778-5793. https://doi.org/10.1109/jiot.2022.3151201

Unmanned-aerial-vehicle (UAV)-assisted data collection has been emerging as a prominent application due to its flexibility, mobility, and low operational cost. However, under the dynamic and uncertainty of Internet of Things data collection and energ... Read More about Joint Speed Control and Energy Replenishment Optimization for UAV-Assisted IoT Data Collection With Deep Reinforcement Transfer Learning.

Dynamic Optimal Coding and Scheduling for Distributed Learning over Wireless Edge Networks (2021)
Conference Proceeding
Van Huynh, N., Hoang, D. T., Nguyen, D. N., & Dutkiewicz, E. (2021). Dynamic Optimal Coding and Scheduling for Distributed Learning over Wireless Edge Networks. In 2021 IEEE Global Communications Conference (GLOBECOM). https://doi.org/10.1109/globecom46510.2021.9685719

This paper proposes a novel framework that can effectively address key challenges for the development of distributed learning over wireless edge networks. In particular, we first introduce a highly effective distributed learning model leveraging the... Read More about Dynamic Optimal Coding and Scheduling for Distributed Learning over Wireless Edge Networks.

Joint Coding and Scheduling Optimization for Distributed Learning Over Wireless Edge Networks (2021)
Journal Article
Van Huynh, N., Hoang, D. T., Nguyen, D. N., & Dutkiewicz, E. (2022). Joint Coding and Scheduling Optimization for Distributed Learning Over Wireless Edge Networks. IEEE Journal on Selected Areas in Communications, 40(2), 484-498. https://doi.org/10.1109/jsac.2021.3118432

Unlike theoretical analysis of distributed learning (DL) in the literature, DL over wireless edge networks faces the inherent dynamics/uncertainty of wireless connections and edge nodes, making DL less efficient or even inapplicable under the highly... Read More about Joint Coding and Scheduling Optimization for Distributed Learning Over Wireless Edge Networks.

Defeating Reactive Jammers with Deep Dueling-based Deception Mechanism (2021)
Conference Proceeding
Van Huynh, N., Nguyen, D. N., Hoang, D. T., & Dutkiewicz, E. (2021). Defeating Reactive Jammers with Deep Dueling-based Deception Mechanism. In ICC 2021 - IEEE International Conference on Communications. https://doi.org/10.1109/icc42927.2021.9500391

Conventional anti-jamming solutions like frequency hopping and rate adaptation that are more suitable for proactive jammers are not effective in dealing with reactive jammers. These advanced jammers with recent advances in signal detection can discer... Read More about Defeating Reactive Jammers with Deep Dueling-based Deception Mechanism.

Optimal Beam Association for High Mobility mmWave Vehicular Networks: Lightweight Parallel Reinforcement Learning Approach (2021)
Journal Article
Van Huynh, N., Nguyen, D. N., Hoang, D. T., & Dutkiewicz, E. (2021). Optimal Beam Association for High Mobility mmWave Vehicular Networks: Lightweight Parallel Reinforcement Learning Approach. IEEE Transactions on Communications, 69(9), 5948-5961. https://doi.org/10.1109/tcomm.2021.3088305

In intelligent transportation systems (ITS), vehicles are expected to feature with advanced applications and services which demand ultra-high data rates and low-latency communications. For that, the millimeter wave (mmWave) communication has been eme... Read More about Optimal Beam Association for High Mobility mmWave Vehicular Networks: Lightweight Parallel Reinforcement Learning Approach.

DeepFake: Deep Dueling-Based Deception Strategy to Defeat Reactive Jammers (2021)
Journal Article
Van Huynh, N., Hoang, D. T., Nguyen, D. N., & Dutkiewicz, E. (2021). DeepFake: Deep Dueling-Based Deception Strategy to Defeat Reactive Jammers. IEEE Transactions on Wireless Communications, 20(10), 6898-6914. https://doi.org/10.1109/twc.2021.3078439

In this paper, we introduce DeepFake, a novel deep reinforcement learning-based deception strategy to deal with reactive jamming attacks. In particular, for a smart and reactive jamming attack, the jammer is able to sense the channel and attack the c... Read More about DeepFake: Deep Dueling-Based Deception Strategy to Defeat Reactive Jammers.

Time Scheduling and Energy Trading for Heterogeneous Wireless-Powered and Backscattering-Based IoT Networks (2021)
Journal Article
Nguyen, N., Nguyen, D. N., Hoang, D. T., Van Huynh, N., Dutkiewicz, E., Nguyen, N., & Nguyen, Q. (2021). Time Scheduling and Energy Trading for Heterogeneous Wireless-Powered and Backscattering-Based IoT Networks. IEEE Transactions on Wireless Communications, 20(10), 6835-6851. https://doi.org/10.1109/twc.2021.3077018

This article studies the strategic interactions between an IoT service provider (IoTSP) which consists of heterogeneous IoT devices and its energy service provider (ESP). To that end, we propose an economic framework using the Stackelberg game to max... Read More about Time Scheduling and Energy Trading for Heterogeneous Wireless-Powered and Backscattering-Based IoT Networks.

Fast or Slow: An Autonomous Speed Control Approach for UAV-assisted IoT Data Collection Networks (2021)
Conference Proceeding
Chu, N. H., Hoang, D. T., Nguyen, D. N., Huynh, N. V., & Dutkiewicz, E. (2021). Fast or Slow: An Autonomous Speed Control Approach for UAV-assisted IoT Data Collection Networks. In 2021 IEEE Wireless Communications and Networking Conference (WCNC). https://doi.org/10.1109/wcnc49053.2021.9417563

Unmanned Aerial Vehicles (UAVs) have been emerging as an effective solution for IoT data collection networks thanks to their outstanding flexibility, mobility, and low operation costs. However, due to the limited energy and uncertainty from the data... Read More about Fast or Slow: An Autonomous Speed Control Approach for UAV-assisted IoT Data Collection Networks.

Optimal Beam Association in mmWave Vehicular Networks with Parallel Reinforcement Learning (2020)
Conference Proceeding
Van Huynh, N., Nguyen, D. N., Hoang, D. T., & Dutkiewicz, E. (2020). Optimal Beam Association in mmWave Vehicular Networks with Parallel Reinforcement Learning. In GLOBECOM 2020 - 2020 IEEE Global Communications Conference. https://doi.org/10.1109/globecom42002.2020.9348240

This paper develops a beam association framework for mm Wave vehicular networks to improve the system performance in terms of handover, disconnection time, and data rate under the high mobility of vehicles. In particular, we recruit the semi Markov d... Read More about Optimal Beam Association in mmWave Vehicular Networks with Parallel Reinforcement Learning.

Energy Trading and Time Scheduling for Energy-Efficient Heterogeneous Low-Power IoT Networks (2020)
Conference Proceeding
Nguyen, N., Nguyen, D. N., Hoang, D. T., Van Huynh, N., Nguyen, H., Nguyen, Q. T., & Dutkiewicz, E. (2020). Energy Trading and Time Scheduling for Energy-Efficient Heterogeneous Low-Power IoT Networks. In GLOBECOM 2020 - 2020 IEEE Global Communications Conference. https://doi.org/10.1109/globecom42002.2020.9322418

In this paper, an economic model is proposed to jointly optimize profits for participants in a heterogeneous IoT wireless-powered backscatter communication network. In the network under considerations, a power beacon and IoT devices (with various com... Read More about Energy Trading and Time Scheduling for Energy-Efficient Heterogeneous Low-Power IoT Networks.

A Comprehensive Survey of Enabling and Emerging Technologies for Social Distancing—Part II: Emerging Technologies and Open Issues (2020)
Journal Article
Nguyen, C. T., Saputra, Y. M., Van Huynh, N., Nguyen, N., Khoa, T. V., Tuan, B. M., …Ottersten, B. (2020). A Comprehensive Survey of Enabling and Emerging Technologies for Social Distancing—Part II: Emerging Technologies and Open Issues. IEEE Access, 8, 154209-154236. https://doi.org/10.1109/access.2020.3018124

This two-part paper aims to provide a comprehensive survey on how emerging technologies, e.g., wireless and networking, artificial intelligence (AI) can enable, encourage, and even enforce social distancing practice. In Part I, an extensive backgroun... Read More about A Comprehensive Survey of Enabling and Emerging Technologies for Social Distancing—Part II: Emerging Technologies and Open Issues.

A Comprehensive Survey of Enabling and Emerging Technologies for Social Distancing—Part I: Fundamentals and Enabling Technologies (2020)
Journal Article
Nguyen, C. T., Saputra, Y. M., Huynh, N. V., Nguyen, N., Khoa, T. V., Tuan, B. M., …Ottersten, B. (2020). A Comprehensive Survey of Enabling and Emerging Technologies for Social Distancing—Part I: Fundamentals and Enabling Technologies. IEEE Access, 8, 153479-153507. https://doi.org/10.1109/access.2020.3018140

Social distancing plays a pivotal role in preventing the spread of viral diseases illnesses such as COVID-19. By minimizing the close physical contact among people, we can reduce the chances of catching the virus and spreading it across the community... Read More about A Comprehensive Survey of Enabling and Emerging Technologies for Social Distancing—Part I: Fundamentals and Enabling Technologies.

Defeating Smart and Reactive Jammers with Unlimited Power (2020)
Conference Proceeding
Huynh, N. V., Hoang, D. T., Nguyen, D. N., Dutkiewicz, E., & Mueck, M. (2020). Defeating Smart and Reactive Jammers with Unlimited Power. In 2020 IEEE Wireless Communications and Networking Conference (WCNC). https://doi.org/10.1109/wcnc45663.2020.9120650

Among all wireless jammers, dealing with reactive ones is most challenging. This kind of jammer attacks the channel whenever it detects transmission from legitimate radios. With recent advances in self-interference suppression or in-band full-duplex... Read More about Defeating Smart and Reactive Jammers with Unlimited Power.

Ambient Backscatter Communication Networks (2020)
Book
Hoang, D. T., Niyato, D., Kim, D. I., Huynh, N. V., & Gong, S. (2020). Ambient Backscatter Communication Networks. Cambridge: Cambridge University Press. https://doi.org/10.1017/9781108691383

Understand the fundamental principles and applications of ambient backscatter technology with this authoritative review. Covering both theory and practical engineering, leading researchers describe and explain hardware design, network design, and sig... Read More about Ambient Backscatter Communication Networks.