@article{moy:hal-02956350,
TITLE = {Decentralized spectrum learning for radio collision mitigation in ultra-dense IoT networks: LoRaWAN case study and experiments},
AUTHOR = {Moy, Christophe and Besson, Lilian and Delbarre, Guillaume and Toutain, Laurent},
URL = {https://hal.science/hal-02956350},
JOURNAL = {Annals of Telecommunications - annales des t{\'e}l{\'e}communications},
PUBLISHER = {Springer},
VOLUME = {75},
NUMBER = {11-12},
PAGES = {711-727},
YEAR = {2020},
DOI = {10.1007/s12243-020-00795-y},
KEYWORDS = {Internet of Things (IoT) ; Machine learning ; MAB ; Bandit ; UCB ; Radio spectrum ; Collision mitigation ; Interference ; LoRa ; Artificial intelligence ; LoRaWAN ; Cognitive radio ; Spectrum scarcity ; ISM band},
PDF = {https://hal.science/hal-02956350/file/Moy2020_Article_DecentralizedSpectrumLearningF.pdf},
HAL_ID = {hal-02956350},
HAL_VERSION = {v1},
}