Deep Reinforcement Learning-Based Resource Allocation for QoE Enhancement in Wireless VR Communications
Wireless virtual reality (VR) communication applications have emerged as a transformative technology, offering innovative solutions in various areas of everyday life. However, the successful deployment of these applications faces challenges in ensuring high quality of experience (QoE), especially in...
Saved in:
Main Authors: | Georgios Kougioumtzidis, Vladimir K. Poulkov, Pavlos I. Lazaridis, Zaharias D. Zaharis |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2025-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10870218/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
In silico analysis of human herpes virus-8 genome: a comparison of the K1, VR1, and VR2 regions for genotyping and global geographical distribution
by: Nastaran Khodadad, et al.
Published: (2025-01-01) -
Modelled Energy Cost Minimization Solution for Wireless Rechargeable Sensor Networks
by: Musa Ahmed, et al.
Published: (2025-02-01) -
A critical review of compensation converters for capacitive power transfer in wireless electric vehicle charging circuit topologies
by: Mohammad Amir, et al.
Published: (2025-04-01) -
iFPH: WIRELESS CONTROL OF SOUND
by: Adrian BORZA
Published: (2012-12-01) -
Global Discussion on Life Cycle Assessment Allocation Methods for Recycled Fibers
by: Ivana Azuaje, et al.
Published: (2025-02-01)