Energy-Efficient Mode Selection and Resource Allocation for D2D-Enabled Heterogeneous Networks: A Deep Reinforcement Learning Approach.
Tao ZhangKun ZhuJunhua WangPublished in: IEEE Trans. Wirel. Commun. (2021)
Keyphrases
- resource allocation
- energy efficient
- heterogeneous networks
- mode selection
- reinforcement learning
- wireless sensor networks
- energy consumption
- rate distortion
- sensor networks
- resource management
- motion estimation
- multiple types
- energy efficiency
- base station
- macroblock
- multi agent
- communication networks
- social networks
- optimal allocation
- learning algorithm
- data transmission
- unequal error protection
- state space
- routing protocol
- video coding
- routing algorithm
- response time
- multimedia services
- supervised learning