Projects per year
Abstract
Original language | English |
---|---|
Article number | 8954939 |
Pages (from-to) | 2268-2281 |
Journal | IEEE Transactions on Wireless Communications |
Volume | 19 |
Issue number | 4 |
DOIs | |
Publication status | Published - Apr 2020 |
MoE publication type | A1 Journal article-refereed |
Funding
This work was supported in part by the Academy of Finland under Grant 319759, Grant 319758, and Grant 289611, in part by the National Key Research and Development Program of China under Grant 2017YFB1301003, in part by the National Natural Science Foundation of China under Grant 61701439 and Grant 61731002, in part by the Zhejiang Key Research and Development Plan under Grant 2019C01002, in part by the Japan Society for the Promotion of Science (JSPS) KAKENHI under Grant 18KK0279, Grant 18K18036, and Grant 19H04092, and in part by the Telecommunications Advanced Foundation.
Keywords
- deep reinforcement learning
- long short-term memory
- Markov decision process
- multi-user resource scheduling
- Q-function decomposition
- Vehicular communications
Fingerprint
Dive into the research topics of 'Age of Information Aware Radio Resource Management in Vehicular Networks: A Proactive Deep Reinforcement Learning Perspective'. Together they form a unique fingerprint.Projects
- 2 Finished
-
MISSION: Mission-Critical Internet of Things Applications over Fog Networks
Chen, X. (CoPI), Forsell, M. (Participant), Chen, T. (Participant) & Räty, T. (Participant)
1/01/19 → 31/12/21
Project: Academy of Finland project
-
5G-DRIVE: 5G HarmoniseD Research and TrIals for serVice Evolution between EU and China
Chen, T. (Manager), Horsmanheimo, S. (Participant), Tuomimäki, L. (Participant), Chen, X. (Participant), Zidbeck, J. (Participant), Kutila, M. (Participant), Kauvo, K. (Participant), Mehnert, S. (Participant), Pyykönen, P. (Participant) & Jokela, M. (Participant)
1/09/18 → 30/06/21
Project: EU project