The Frontiers of Deep Reinforcement Learning for Resource Management in Future Wireless HetNets: Techniques, Challenges, and Research Directions
<p dir="ltr">Next generation wireless networks are expected to be extremely complex due to their massive heterogeneity in terms of the types of network architectures they incorporate, the types and numbers of smart IoT devices they serve, and the types of emerging applications they s...
محفوظ في:
| المؤلف الرئيسي: | Abdulmalik Alwarafy (17984104) (author) |
|---|---|
| مؤلفون آخرون: | Mohamed Abdallah (3073191) (author), Bekir Sait Ciftler (17541801) (author), Ala Al-Fuqaha (4434340) (author), Mounir Hamdi (14150652) (author) |
| منشور في: |
2022
|
| الموضوعات: | |
| الوسوم: |
إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!
|
مواد مشابهة
-
Optimal Trajectory and Positioning of UAVs for Small Cell HetNets: Geometrical Analysis and Reinforcement Learning Approach
حسب: Mohammad Taghi Dabiri (16904658)
منشور في: (2023) -
Modified MCP-Based Modeling and Performance Analysis of 3-D Cellular Networks
حسب: Dorsaf Ghozlani (22502816)
منشور في: (2025) -
SWIPT-Enabled Relaying Networks for Next-Generation Wireless Systems: A Review of Achievable Rates and Future Challenges
حسب: Zaino, Rami
منشور في: (2025) -
Deep Reinforcement Learning for Internet of Drones Networks: Issues and Research Directions
حسب: Noor Aboueleneen (17984101)
منشور في: (2023) -
On Efficient Channel Modeling for Video Transmission over Cognitive Radio Networks
حسب: Hassan, Mohamed
منشور في: (2016)