Search Results for author: Muhammad Asad Ullah

Found 1 papers, 0 papers with code

Energy Efficiency Optimization for Subterranean LoRaWAN Using A Reinforcement Learning Approach: A Direct-to-Satellite Scenario

no code implementations3 Nov 2023 Kaiqiang Lin, Muhammad Asad Ullah, Hirley Alves, Konstantin Mikhaylov, Tong Hao

The integration of subterranean LoRaWAN and non-terrestrial networks (NTN) delivers substantial economic and societal benefits in remote agriculture and disaster rescue operations.

Reinforcement Learning (RL)

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