N. Sornin, M. Luis, T. Eirich, and A. L. Beylot, LoRaWAN specification, 2015.

C. Fourtet, The technical challenge of future IoT networks and their consequences on modem's and SoC's design, 2015.

C. Moy, IoTligent: first world-wide Implementation of decentralized spectrum learning for IoT wireless networks, URSI AP-RASC, pp.9-14, 2019.
URL : https://hal.archives-ouvertes.fr/hal-02093350

W. Jouini, D. Ernst, C. Moy, and J. Palicot, Multi-armed bandit based policies for cognitive radio's decision making issues, Signal Circuits and Systems Conference, pp.6-8, 2009.

W. Jouini, D. Ernst, C. Moy, J. Palicot, and ;. I-e-e-e-i-c-c, Upper confidence bound based decision making strategies and dynamic spectrum a c c e s s, Communications, 2010.

T. L. Lai and H. Robbins, Asymptotically efficient adaptive allocation rules, Adv Appl Math, vol.6, issue.1, pp.4-22, 1985.

P. Auer, N. Cesa-bianchi, and P. Fischer, Finite-time analysis of the multiarmed bandit problem, Mach Learn, vol.47, pp.2-3, 2002.

C. Moy, Reinforcement learning real experiments for opportunistic spectrum access, Karlsruhe Workshop on Software Radio, 2014.
URL : https://hal.archives-ouvertes.fr/hal-00994975

R. Bonnefoi, L. Besson, C. Moy, E. Kaufman, and J. Palicot, Multiarmed bandit learning in IoT networks: learning helps even in nonstationary settings, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01575419

A. Anandkumar, N. Michael, A. K. Tang, and A. Swami, Distributed algorithms for learning and cognitive medium access with logarithmic regret, IEEE J Selected Areas Commun, vol.29, issue.4, 2011.

H. Robbins, Some aspects of the sequential design of experiments, Bull Am Math Soc, vol.58, issue.5, pp.527-535, 1952.

Q. Zhao and B. Sadler, A survey of dynamic spectrum access, IEEE Signal Processing and Magazine, 2007.

S. Bubeck and N. Cesa-bianchi, Regret analysis of stochastic and non-stochastic multi-armed bandit problems, Found Trends® Mach Learn, vol.5, issue.1, pp.1-122, 2012.

L. Besson, Multi-players algorithms for Internet of Things networks, 2019.
URL : https://hal.archives-ouvertes.fr/tel-02491380

W. R. Thompson, On the likelihood that one unknown probability exceeds another in view of the evidence of two samples, Biometrika, vol.5, 1933.

C. Moy, J. Palicot, and D. Sj, Proof-of-concept system for opportunistic spectrum access in multi-user decentralized networks, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01458815

L. Besson, SMPyBandits: an open-source research framework for single and multi-players multi-arms bandits (MAB) algorithms in Python, p.2020

L. Besson, R. Bonnefoi, and C. Moy, MALIN: multi-armed bandit learning for Iot networks with GRC: a TestBed implementation and demonstration that Learning Helps. ICT, France 19. LoRaWAN?, (2017) v1.1 Specification, p.2020, 2018.

C. Moy and L. Besson, Decentralized spectrum learning for IoT wireless networks collision mitigation, First International Workshop on Intelligent Systems for the Internet of Things, pp.29-31, 2019.
URL : https://hal.archives-ouvertes.fr/hal-02144465