Deep Reinforcement Learning for LoRa Localization
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This talk presents a deep reinforcement learning (DRL) solution for LoRa localization. It addresses the challenges of accurate localization with LoRa technology. Specifically, I presented a novel approach that uses DRL to optimize the assignment of spreading factors (SFs) in LoRa networks to improve localization accuracy. The results of the research demonstrate that the DRL-based approach achieves superior localization accuracy compared to benchmark methods.