scholarly journals Energy Efficiency Optimization and Dynamic Mode Selection Algorithms for D2D Communication Under HetNet in Downlink Reuse

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 95251-95265
Author(s):  
Amal Ali Algedir ◽  
Hazem H. Refai
Keyword(s):  
Energy Efficiency ◽  
Mode Selection ◽  
D2d Communication ◽  
Dynamic Mode ◽  
Efficiency Optimization ◽  
Selection Algorithms

scholarly journals Reinforcement Learning for Energy Optimization with 5G Communications in Vehicular Social Networks

Sensors ◽  
2020 ◽  
Vol 20 (8) ◽  
pp. 2361 ◽  
Author(s):  
Hyebin Park ◽  
Yujin Lim
Keyword(s):  
Social Networks ◽  
Energy Efficiency ◽  
Reinforcement Learning ◽  
Power Control ◽  
Mode Selection ◽  
Energy Optimization ◽  
D2d Communication ◽  
System Capacity ◽  
Connected Vehicles ◽  
Q Learning

Increased data traffic resulting from the increase in the deployment of connected vehicles has become relevant in vehicular social networks (VSNs). To provide efficient communication between connected vehicles, researchers have studied device-to-device (D2D) communication. D2D communication not only reduces the energy consumption and loads of the system but also increases the system capacity by reusing cellular resources. However, D2D communication is highly affected by interference and therefore requires interference-management techniques, such as mode selection and power control. To make an optimal mode selection and power control, it is necessary to apply reinforcement learning that considers a variety of factors. In this paper, we propose a reinforcement-learning technique for energy optimization with fifth-generation communication in VSNs. To achieve energy optimization, we use centralized Q-learning in the system and distributed Q-learning in the vehicles. The proposed algorithm learns to maximize the energy efficiency of the system by adjusting the minimum signal-to-interference plus noise ratio to guarantee the outage probability. Simulations were performed to compare the performance of the proposed algorithm with that of the existing mode-selection and power-control algorithms. The proposed algorithm performed the best in terms of system energy efficiency and achievable data rate.

Energy efficiency optimization of PCM and aerogel-filled multiple glazing windows

Energy ◽  
2021 ◽  
Vol 222 ◽  
pp. 119916
Author(s):  
Shu Zhang ◽  
Wanyu Hu ◽  
Dong Li ◽  
Chengjun Zhang ◽  
Müslüm Arıcı ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Efficiency Optimization
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