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Planification des ressources radio dans les réseaux IoT longues portées avec faible puissance

Abstract : In this thesis, we focus on radio resource planning issues for low power wide area networks based on NB-IoT and LoRa technologies. In both cases, the average behavior of the network is considered by assuming the sensors and the collectors are distributed according to independent random Poisson Point Process marked by the channel randomness. For the NB-IoT, we elaborate a statistical dimensioning model that estimates the number of radio resources in the network depending on the tolerated delay access, the density of active nodes, the collectors, and the antenna configuration with single and multi-user transmission. For the LoRa network, we propose a multi-sub band allocation technique to mitigate the high level of interference induced by nodes that transmit with the same spreading factor. To dynamically allocate the spreading factor and the power, we present a Q-learning multi-agent approach to improve the energy efficiency.
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Submitted on : Wednesday, April 21, 2021 - 2:34:09 PM
Last modification on : Monday, February 21, 2022 - 3:38:11 PM
Long-term archiving on: : Thursday, July 22, 2021 - 6:46:46 PM


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  • HAL Id : tel-03204385, version 1



yi yu. Planification des ressources radio dans les réseaux IoT longues portées avec faible puissance. Traitement du signal et de l'image [eess.SP]. Conservatoire national des arts et metiers - CNAM, 2021. Français. ⟨NNT : 2021CNAM1287⟩. ⟨tel-03204385⟩



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