Publications

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Author Title [ Type(Desc)] Year
Conference Paper
N. Chen, Li, M. , Wang, M. , Su, Z. , Li, J. , and Shen, X. , A Dynamic Pricing Based Scheduling Scheme for Electric Vehicles as Mobile Energy Storages, in IEEE International Conference on Communications (ICC), 2021.
M. Li, Gao, J. , Zhang, N. , Zhao, L. , and Shen, X. , Collaborative Computing in Vehicular Networks: A Deep Reinforcement Learning Approach, in IEEE International Conference on Communications (ICC), virtual/Dublin, Ireland, 2020, pp. 1-6.
M. Li, Gao, J. , Zhao, L. , and Shen, X. , Task Time Allocation and Reward Scheme for PEV Charging Station Advertising, in IEEE International Conference on Communications (ICC), Shanghai, China, 2019, pp. 1-6.
M. Chen, Li, M. , Wang, M. , Ma, J. , and Shen, X. , Compensation of Charging Station Overload via On-road Mobile Energy Storage Scheduling, in IEEE Global Communications Conference (GLOBECOM), Hawaii, USA, 2019, pp. 1-6.
M. Baljon, Li, M. , Liang, H. , and Zhao, L. , SMDP-Based Resource Allocation for Wireless Networks with Energy Harvesting Constraints, in IEEE Vehicular Technology Conference (VTC-Fall), Toronto, Canada, 2017, pp. 1-5.
J. Gao, Li, M. , He, P. , and Zhao, L. , Incentive for Distributed Optimization in Multi-User Network: A Study of Two Scenarios, in IEEE Vehicular Technology Conference (VTC-Fall), Toronto, Canada, 2017.
M. Li and Zhao, L. , A Decentralized Load Balancing Approach for Neighbouring Charging Stationsvia EV Fleets, in IEEE Vehicular Technology Conference (VTC-Fall), Toronto, Canada, 2017, pp. 1-5.
M. Li, He, P. , and Zhao, L. , Dynamic Elastic Load Scheduling Achieving Load Balancing for Smart Grid, in IEEE/CIC International Conference on Communications in China (ICCC), Chengdu, China, 2016, pp. 1-6.
L. Ferdouse, Li, M. , Guan, L. , and Anpalagan, A. , Bayesian Workload Scheduling in Multimedia Cloud Networks, in IEEE International Workshop on Computer Aided Modelling and Design of Communication Links and Networks (CAMAD), Toronto, Canada, 2016, pp. 1-6.
Journal
J. Gao, Zhuang, W. , Li, M. , Shen, X. , and Li, X. , MAC for Machine-Type Communications in Industrial IoT - Part I: Protocol Design and Analysis, vol. 8, no. 12. pp. 9945-9957, 2021.
Journal Article
X. Shen, Gao, J. , Wu, W. , Li, M. , Zhou, C. , and Zhuang, W. , Holistic Network Virtualization and Pervasive Network Intelligence for 6G, IEEE Communications Surveys and Tutorials, pp. 1-22, Submitted.
W. Wu et al., AI-Native NetworkSlicing for 6G Networks, Submitted to IEEE Wireless Communication, pp. 1-8, Submitted.
M. Li, Gao, J. , Zhou, C. , Shen, X. , and Zhuang, W. , Slicing-Based AI Service Provisioning on Network Edge, Submitted to IEEE Vehicular Technology Magazine, pp. 1-8, Submitted.
H. Liang et al., Reinforcement Learning Enabled Dynamic Resource Allocation in the Internet of Vehicles, IEEE Transactions on Industrial Informatics, vol. 17, no. 7, pp. 4957-4967, 2021.
W. Wu et al., Dynamic RAN Slicing for Service-Oriented Vehicular Networks via Constrained Learning, IEEE Journal on Selected Areas in Communications, vol. 39, no. 7, pp. 2076-2089, 2021.
J. Gao, Li, M. , Zhuang, W. , Shen, X. , and Li, X. , MAC for Machine-Type Communications in Industrial IoT - Part II: Scheduling and Numerical Results, IEEE Internet of Things Journal, vol. 8, no. 12, pp. 9958 - 9969, 2021.
M. Li, Gao, J. , Zhao, L. , and Shen, X. , Adaptive Computing Scheduling for Edge-assisted Autonomous Driving, IEEE Transactions on Vehicular Technology, pp. 1-12, 2021.
X. Shen et al., AI-Assisted Network-SlicingBased Next-Generation Wireless Networks, IEEE Open Journal of Vehicular Technology, vol. 1, pp. 45-66, 2020.
M. Li, Gao, J. , Chen, N. , Zhao, L. , and Shen, X. , Decentralized PEV Power Allocation with Power Distribution and Transportation Constraints, IEEE Journal on Selected Areas in Communications, vol. 38, no. 1, pp. 229-243, 2020.
M. Li, Cheng, N. , Gao, J. , Wang, Y. , Zhao, L. , and Shen, X. , Energy-Efficient UAV-Assisted MobileEdge Computing: Resource Allocation and Trajectory Optimization, IEEE Transactions on Vehicular Technology, vol. 69, no. 3, pp. 3424-3438, 2020.

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