Get our free extension to see links to code for papers anywhere online!

Chrome logo Add to Chrome

Firefox logo Add to Firefox
Picture for Dusit Niyato

Dusit Niyato

Spectrum Learning-Aided Reconfigurable Intelligent Surfaces for 'Green' 6G Networks


Sep 03, 2021
Bo Yang, Xuelin Cao, Chongwen Huang, Yong Liang Guan, Chau Yuen, Marco Di Renzo, Dusit Niyato, Merouane Debbah, Lajos Hanzo

Figure 1 for Spectrum Learning-Aided Reconfigurable Intelligent Surfaces for 'Green' 6G Networks
Figure 2 for Spectrum Learning-Aided Reconfigurable Intelligent Surfaces for 'Green' 6G Networks
Figure 3 for Spectrum Learning-Aided Reconfigurable Intelligent Surfaces for 'Green' 6G Networks

  Access Paper or Ask Questions

6G Internet of Things: A Comprehensive Survey


Aug 11, 2021
Dinh C. Nguyen, Ming Ding, Pubudu N. Pathirana, Aruna Seneviratne, Jun Li, Dusit Niyato, Octavia Dobre, H. Vincent Poor

Figure 1 for 6G Internet of Things: A Comprehensive Survey
Figure 2 for 6G Internet of Things: A Comprehensive Survey
Figure 3 for 6G Internet of Things: A Comprehensive Survey
Figure 4 for 6G Internet of Things: A Comprehensive Survey
* Accepted at IEEE Internet of Things Journal, 25 pages 
  Access Paper or Ask Questions

Risk Adversarial Learning System for Connected and Autonomous Vehicle Charging


Aug 02, 2021
Md. Shirajum Munir, Ki Tae Kim, Kyi Thar, Dusit Niyato, Choong Seon Hong

Figure 1 for Risk Adversarial Learning System for Connected and Autonomous Vehicle Charging
Figure 2 for Risk Adversarial Learning System for Connected and Autonomous Vehicle Charging
Figure 3 for Risk Adversarial Learning System for Connected and Autonomous Vehicle Charging
Figure 4 for Risk Adversarial Learning System for Connected and Autonomous Vehicle Charging
* Submitted to IEEE publisher for peer review 
  Access Paper or Ask Questions

Optimal Power Allocation for Rate Splitting Communications with Deep Reinforcement Learning


Jul 01, 2021
Nguyen Quang Hieu, Dinh Thai Hoang, Dusit Niyato, Dong In Kim

Figure 1 for Optimal Power Allocation for Rate Splitting Communications with Deep Reinforcement Learning
Figure 2 for Optimal Power Allocation for Rate Splitting Communications with Deep Reinforcement Learning
Figure 3 for Optimal Power Allocation for Rate Splitting Communications with Deep Reinforcement Learning
Figure 4 for Optimal Power Allocation for Rate Splitting Communications with Deep Reinforcement Learning

  Access Paper or Ask Questions

Optimal Status Update for Caching Enabled IoT Networks: A Dueling Deep R-Network Approach


Jun 13, 2021
Chao Xu, Yiping Xie, Xijun Wang, Howard H. Yang, Dusit Niyato, Tony Q. S. Quek

Figure 1 for Optimal Status Update for Caching Enabled IoT Networks: A Dueling Deep R-Network Approach
Figure 2 for Optimal Status Update for Caching Enabled IoT Networks: A Dueling Deep R-Network Approach
Figure 3 for Optimal Status Update for Caching Enabled IoT Networks: A Dueling Deep R-Network Approach
Figure 4 for Optimal Status Update for Caching Enabled IoT Networks: A Dueling Deep R-Network Approach

  Access Paper or Ask Questions

Converged Reconfigurable Intelligent Surface and Mobile Edge Computing for Space Information Networks


Jun 08, 2021
Xuelin Cao, Bo Yang, Chongwen Huang, Chau Yuen, Yan Zhang, Dusit Niyato, Zhu Han

Figure 1 for Converged Reconfigurable Intelligent Surface and Mobile Edge Computing for Space Information Networks
Figure 2 for Converged Reconfigurable Intelligent Surface and Mobile Edge Computing for Space Information Networks
Figure 3 for Converged Reconfigurable Intelligent Surface and Mobile Edge Computing for Space Information Networks
Figure 4 for Converged Reconfigurable Intelligent Surface and Mobile Edge Computing for Space Information Networks

  Access Paper or Ask Questions

Federated Learning for Industrial Internet of Things in Future Industries


May 31, 2021
Dinh C. Nguyen, Ming Ding, Pubudu N. Pathirana, Aruna Seneviratne, Jun Li, Dusit Niyato, H. Vincent Poor

Figure 1 for Federated Learning for Industrial Internet of Things in Future Industries
Figure 2 for Federated Learning for Industrial Internet of Things in Future Industries
Figure 3 for Federated Learning for Industrial Internet of Things in Future Industries
Figure 4 for Federated Learning for Industrial Internet of Things in Future Industries
* Accepted at IEEE Wireless Communications Magazine 
  Access Paper or Ask Questions

Transferable Deep Reinforcement Learning Framework for Autonomous Vehicles with Joint Radar-Data Communications


May 28, 2021
Nguyen Quang Hieu, Dinh Thai Hoang, Dusit Niyato, Ping Wang, Dong In Kim, Chau Yuen

Figure 1 for Transferable Deep Reinforcement Learning Framework for Autonomous Vehicles with Joint Radar-Data Communications
Figure 2 for Transferable Deep Reinforcement Learning Framework for Autonomous Vehicles with Joint Radar-Data Communications
Figure 3 for Transferable Deep Reinforcement Learning Framework for Autonomous Vehicles with Joint Radar-Data Communications
Figure 4 for Transferable Deep Reinforcement Learning Framework for Autonomous Vehicles with Joint Radar-Data Communications

  Access Paper or Ask Questions

Throughput Maximization for IRS-Assisted Wireless Powered Hybrid NOMA and TDMA


Apr 27, 2021
Dingcai Zhang, Qingqing Wu, Miao Cui, Guangchi Zhang, Dusit Niyato

Figure 1 for Throughput Maximization for IRS-Assisted Wireless Powered Hybrid NOMA and TDMA
Figure 2 for Throughput Maximization for IRS-Assisted Wireless Powered Hybrid NOMA and TDMA
* 10 pages, 5 figures, submitted to IEEE WCL 
  Access Paper or Ask Questions

A Joint Energy and Latency Framework for Transfer Learning over 5G Industrial Edge Networks


Apr 19, 2021
Bo Yang, Omobayode Fagbohungbe, Xuelin Cao, Chau Yuen, Lijun Qian, Dusit Niyato, Yan Zhang

Figure 1 for A Joint Energy and Latency Framework for Transfer Learning over 5G Industrial Edge Networks

  Access Paper or Ask Questions

Optimizing the Long-Term Average Reward for Continuing MDPs: A Technical Report


Apr 14, 2021
Chao Xu, Yiping Xie, Xijun Wang, Howard H. Yang, Dusit Niyato, Tony Q. S. Quek

Figure 1 for Optimizing the Long-Term Average Reward for Continuing MDPs: A Technical Report

  Access Paper or Ask Questions

Federated Learning Meets Blockchain in Edge Computing: Opportunities and Challenges


Apr 05, 2021
Dinh C. Nguyen, Ming Ding, Quoc-Viet Pham, Pubudu N. Pathirana, Long Bao Le, Aruna Seneviratne, Jun Li, Dusit Niyato, H. Vincent Poor

Figure 1 for Federated Learning Meets Blockchain in Edge Computing: Opportunities and Challenges
Figure 2 for Federated Learning Meets Blockchain in Edge Computing: Opportunities and Challenges
Figure 3 for Federated Learning Meets Blockchain in Edge Computing: Opportunities and Challenges
Figure 4 for Federated Learning Meets Blockchain in Edge Computing: Opportunities and Challenges
* Accepted at the IEEE Internet of Things Journal, 19 pages 
  Access Paper or Ask Questions

Learning Rate Optimization for Federated Learning Exploiting Over-the-air Computation


Mar 01, 2021
Chunmei Xu, Shengheng Liu, Zhaohui Yang, Yongming Huang, Dusit Niyato, Kai-Kit Wong

Figure 1 for Learning Rate Optimization for Federated Learning Exploiting Over-the-air Computation
Figure 2 for Learning Rate Optimization for Federated Learning Exploiting Over-the-air Computation
Figure 3 for Learning Rate Optimization for Federated Learning Exploiting Over-the-air Computation
Figure 4 for Learning Rate Optimization for Federated Learning Exploiting Over-the-air Computation

  Access Paper or Ask Questions

Transfer Learning for Future Wireless Networks: A Comprehensive Survey


Feb 15, 2021
Cong T. Nguyen, Nguyen Van Huynh, Nam H. Chu, Yuris Mulya Saputra, Dinh Thai Hoang, Diep N. Nguyen, Quoc-Viet Pham, Dusit Niyato, Eryk Dutkiewicz, Won-Joo Hwang

Figure 1 for Transfer Learning for Future Wireless Networks: A Comprehensive Survey
Figure 2 for Transfer Learning for Future Wireless Networks: A Comprehensive Survey
Figure 3 for Transfer Learning for Future Wireless Networks: A Comprehensive Survey
Figure 4 for Transfer Learning for Future Wireless Networks: A Comprehensive Survey

  Access Paper or Ask Questions

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


Dec 23, 2020
Helin Yang, Zehui Xiong, Jun Zhao, Dusit Niyato, Qingqing Wu, Massimo Tornatore, Stefano Secci

Figure 1 for Intelligent Reflecting Surface Assisted Anti-Jamming Communications Based on Reinforcement Learning
Figure 2 for Intelligent Reflecting Surface Assisted Anti-Jamming Communications Based on Reinforcement Learning
Figure 3 for Intelligent Reflecting Surface Assisted Anti-Jamming Communications Based on Reinforcement Learning
Figure 4 for Intelligent Reflecting Surface Assisted Anti-Jamming Communications Based on Reinforcement Learning
* This paper appears in the Proceedings of IEEE Global Communications Conference (GLOBECOM) 2020. A full version appears in IEEE Transactions on Wireless Communications. arXiv:2004.12539 
  Access Paper or Ask Questions

A Comprehensive Survey of 6G Wireless Communications


Dec 21, 2020
Yang Zhao, Wenchao Zhai, Jun Zhao, Tinghao Zhang, Sumei Sun, Dusit Niyato, Kwok-Yan Lam

Figure 1 for A Comprehensive Survey of 6G Wireless Communications
Figure 2 for A Comprehensive Survey of 6G Wireless Communications
Figure 3 for A Comprehensive Survey of 6G Wireless Communications
Figure 4 for A Comprehensive Survey of 6G Wireless Communications

  Access Paper or Ask Questions

Towards Communication-efficient and Attack-Resistant Federated Edge Learning for Industrial Internet of Things


Dec 08, 2020
Yi Liu, Ruihui Zhao, Jiawen Kang, Abdulsalam Yassine, Dusit Niyato, Jialiang Peng

Figure 1 for Towards Communication-efficient and Attack-Resistant Federated Edge Learning for Industrial Internet of Things
Figure 2 for Towards Communication-efficient and Attack-Resistant Federated Edge Learning for Industrial Internet of Things
Figure 3 for Towards Communication-efficient and Attack-Resistant Federated Edge Learning for Industrial Internet of Things
Figure 4 for Towards Communication-efficient and Attack-Resistant Federated Edge Learning for Industrial Internet of Things

  Access Paper or Ask Questions

Optimization-driven Machine Learning for Intelligent Reflecting Surfaces Assisted Wireless Networks


Aug 29, 2020
Shimin Gong, Jiaye Lin, Jinbei Zhang, Dusit Niyato, Dong In Kim, Mohsen Guizani

Figure 1 for Optimization-driven Machine Learning for Intelligent Reflecting Surfaces Assisted Wireless Networks
Figure 2 for Optimization-driven Machine Learning for Intelligent Reflecting Surfaces Assisted Wireless Networks
Figure 3 for Optimization-driven Machine Learning for Intelligent Reflecting Surfaces Assisted Wireless Networks
Figure 4 for Optimization-driven Machine Learning for Intelligent Reflecting Surfaces Assisted Wireless Networks
* submitted to IEEE Communications Magazine 
  Access Paper or Ask Questions

Toward Smart Security Enhancement of Federated Learning Networks


Aug 19, 2020
Junjie Tan, Ying-Chang Liang, Nguyen Cong Luong, Dusit Niyato

Figure 1 for Toward Smart Security Enhancement of Federated Learning Networks
Figure 2 for Toward Smart Security Enhancement of Federated Learning Networks
Figure 3 for Toward Smart Security Enhancement of Federated Learning Networks
Figure 4 for Toward Smart Security Enhancement of Federated Learning Networks

  Access Paper or Ask Questions

Predictive Maintenance for Edge-Based Sensor Networks: A Deep Reinforcement Learning Approach


Jul 07, 2020
Kevin Shen Hoong Ong, Dusit Niyato, Chau Yuen

Figure 1 for Predictive Maintenance for Edge-Based Sensor Networks: A Deep Reinforcement Learning Approach
Figure 2 for Predictive Maintenance for Edge-Based Sensor Networks: A Deep Reinforcement Learning Approach
Figure 3 for Predictive Maintenance for Edge-Based Sensor Networks: A Deep Reinforcement Learning Approach
Figure 4 for Predictive Maintenance for Edge-Based Sensor Networks: A Deep Reinforcement Learning Approach
* 6 pages, 5 figures, accepted in IEEE WF-IoT 2020 
  Access Paper or Ask Questions

Cognitive Radio Network Throughput Maximization with Deep Reinforcement Learning


Jul 07, 2020
Kevin Shen Hoong Ong, Yang Zhang, Dusit Niyato

Figure 1 for Cognitive Radio Network Throughput Maximization with Deep Reinforcement Learning
Figure 2 for Cognitive Radio Network Throughput Maximization with Deep Reinforcement Learning
Figure 3 for Cognitive Radio Network Throughput Maximization with Deep Reinforcement Learning
Figure 4 for Cognitive Radio Network Throughput Maximization with Deep Reinforcement Learning
* 5 pages, 2 figures, accepted in IEEE VTC-Fall 2019 
  Access Paper or Ask Questions

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


Jun 04, 2020
Yi Liu, Xingliang Yuan, Zehui Xiong, Jiawen Kang, Xiaofei Wang, Dusit Niyato

Figure 1 for Federated Learning for 6G Communications: Challenges, Methods, and Future Directions
Figure 2 for Federated Learning for 6G Communications: Challenges, Methods, and Future Directions
Figure 3 for Federated Learning for 6G Communications: Challenges, Methods, and Future Directions
Figure 4 for Federated Learning for 6G Communications: Challenges, Methods, and Future Directions

  Access Paper or Ask Questions

Incentive Mechanism Design for Resource Sharing in Collaborative Edge Learning


May 31, 2020
Wei Yang Bryan Lim, Jer Shyuan Ng, Zehui Xiong, Dusit Niyato, Cyril Leung, Chunyan Miao, Qiang Yang

Figure 1 for Incentive Mechanism Design for Resource Sharing in Collaborative Edge Learning
Figure 2 for Incentive Mechanism Design for Resource Sharing in Collaborative Edge Learning
Figure 3 for Incentive Mechanism Design for Resource Sharing in Collaborative Edge Learning
Figure 4 for Incentive Mechanism Design for Resource Sharing in Collaborative Edge Learning

  Access Paper or Ask Questions

Optimization-driven Deep Reinforcement Learning for Robust Beamforming in IRS-assisted Wireless Communications


May 25, 2020
Jiaye Lin, Yuze Zou, Xiaoru Dong, Shimin Gong, Dinh Thai Hoang, Dusit Niyato

Figure 1 for Optimization-driven Deep Reinforcement Learning for Robust Beamforming in IRS-assisted Wireless Communications
Figure 2 for Optimization-driven Deep Reinforcement Learning for Robust Beamforming in IRS-assisted Wireless Communications
Figure 3 for Optimization-driven Deep Reinforcement Learning for Robust Beamforming in IRS-assisted Wireless Communications
Figure 4 for Optimization-driven Deep Reinforcement Learning for Robust Beamforming in IRS-assisted Wireless Communications

  Access Paper or Ask Questions

A Secure Federated Learning Framework for 5G Networks


May 12, 2020
Yi Liu, Jialiang Peng, Jiawen Kang, Abdullah M. Iliyasu, Dusit Niyato, Ahmed A. Abd El-Latif

Figure 1 for A Secure Federated Learning Framework for 5G Networks
Figure 2 for A Secure Federated Learning Framework for 5G Networks
Figure 3 for A Secure Federated Learning Framework for 5G Networks
Figure 4 for A Secure Federated Learning Framework for 5G Networks
* This paper was accepted by IEEE Wireless Communications Magazine 
  Access Paper or Ask Questions

Demand-Side Scheduling Based on Deep Actor-Critic Learning for Smart Grids


May 05, 2020
Joash Lee, Wenbo Wang, Dusit Niyato

Figure 1 for Demand-Side Scheduling Based on Deep Actor-Critic Learning for Smart Grids
Figure 2 for Demand-Side Scheduling Based on Deep Actor-Critic Learning for Smart Grids
Figure 3 for Demand-Side Scheduling Based on Deep Actor-Critic Learning for Smart Grids
Figure 4 for Demand-Side Scheduling Based on Deep Actor-Critic Learning for Smart Grids

  Access Paper or Ask Questions

Resource Management for Blockchain-enabled Federated Learning: A Deep Reinforcement Learning Approach


May 01, 2020
Nguyen Quang Hieu, Tran The Anh, Nguyen Cong Luong, Dusit Niyato, Dong In Kim, Erik Elmroth

Figure 1 for Resource Management for Blockchain-enabled Federated Learning: A Deep Reinforcement Learning Approach
Figure 2 for Resource Management for Blockchain-enabled Federated Learning: A Deep Reinforcement Learning Approach
Figure 3 for Resource Management for Blockchain-enabled Federated Learning: A Deep Reinforcement Learning Approach
Figure 4 for Resource Management for Blockchain-enabled Federated Learning: A Deep Reinforcement Learning Approach

  Access Paper or Ask Questions

Local Differential Privacy based Federated Learning for Internet of Things


Apr 19, 2020
Yang Zhao, Jun Zhao, Mengmeng Yang, Teng Wang, Ning Wang, Lingjuan Lyu, Dusit Niyato, Kwok Yan Lam

Figure 1 for Local Differential Privacy based Federated Learning for Internet of Things
Figure 2 for Local Differential Privacy based Federated Learning for Internet of Things
Figure 3 for Local Differential Privacy based Federated Learning for Internet of Things
Figure 4 for Local Differential Privacy based Federated Learning for Internet of Things

  Access Paper or Ask Questions