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What is Access Control in NB-IoT via Reinforcement Learning about?

This paper proposes a deep reinforcement learning strategy to enhance access control in Narrowband-IoT (NB-IoT) networks, addressing the challenges posed by massive Machine Type Communications (MTC) and potential network congestion. By formulating the access problem as a Markov decision process and utilizing the Twin Delayed Deep Deterministic policy gradient algorithm, the authors aim to optimize the blocking factor for device access, demonstrating improved performance over existing methods through simulat

Author

Anbazhagan Selvanathan

Language

EN