Enhanced Reinforcement Learning Algorithm Based-Transmission Parameter Selection for Optimization of Energy Consumption and Packet Delivery Ratio in LoRa Wireless Networks

Wireless communication technologies (WSN) are pivotal for the successful deployment of the Internet of Things (IoT). Among them, long-range (LoRa) and long-range wide-area network (LoRaWAN) technologies have been widely adopted due to their ability to provide long-distance communication, low energy...

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Detaylı Bibliyografya
Asıl Yazarlar:	Batyrbek Zholamanov, Askhat Bolatbek, Ahmet Saymbetov, Madiyar Nurgaliyev, Evan Yershov, Kymbat Kopbay, Sayat Orynbassar, Gulbakhar Dosymbetova, Ainur Kapparova, Nurzhigit Kuttybay, Nursultan Koshkarbay
Materyal Türü:	Artigo
Dil:	Inglês
Baskı/Yayın Bilgisi:	MDPI AG 2024-12-01
Seri Bilgileri:	Journal of Sensor and Actuator Networks
Konular:	LoRaWAN wireless sensor networks packet delivery ratio reinforcement learning Double Deep Q-Network with Prioritized Experience Replay (DDQN-PER) transmission parameter selection
Online Erişim:	https://www.mdpi.com/2224-2708/13/6/89
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Enhanced Reinforcement Learning Algorithm Based-Transmission Parameter Selection for Optimization of Energy Consumption and Packet Delivery Ratio in LoRa Wireless Networks

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