Deep Reinforcement Learning Optimizes Power and Time Allocation in CIoT Networks
Published:Dec 17, 2025 04:00
•1 min read
•ArXiv
Analysis
This research explores the application of deep reinforcement learning to enhance the efficiency of communication in the context of Internet of Things (IoT) devices, focusing specifically on simultaneous wireless information and power transfer (SWIPT) and energy harvesting (EH). The work's significance lies in optimizing time and power allocation, critical for prolonging the lifespan and improving the performance of CIoT (Cellular IoT) networks.
Key Takeaways
- •Applies deep reinforcement learning to optimize resource allocation in CIoT networks.
- •Addresses the challenges of SWIPT and EH in resource-constrained environments.
- •Aims to improve network performance and extend the operational lifespan of IoT devices.
Reference
“The research focuses on Simultaneous Wireless Information and Power Transfer (SWIPT) and Energy Harvesting (EH) in CIoT.”