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A LoRa simulator with applied multi-armed bandit algorithms.

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IoT-MABs/LoRaSim_MABs

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LoRaSim_MABs

This repository contains an open-source LoRa simulator with applied multi-armed bandit algorithms written in C. The bandit algorithms aim to optimize the Packet Delivery Rate (PDR) and the energy consumption of the nodes in a LoRa network, by selecting the spreading factor (SF) and the transmitting power (TP) of each transmission. Refer to te file "readme.txt" in the repository to run the experiments.

References to the MAB algorithms

  • H. Dakdouk, R. Féraud, R. Laroche, N. Varsier, and P. Maillé. Collaborative exploration and exploitation in massively multi-player bandits.2021.〈hal-03370706〉.
  • H. Dakdouk, R. Féraud, N. Varsier, and P. Maillé. Collaborative exploration in stochastic multi-player bandits. In Asian Conference on Machine Learning, pages 193–208. PMLR, 2020
  • P. Auer, N. Cesa-Bianchi, Y. Freund, and R. E. Schapire. The non-stochastic multi armed bandit problem. SIAM journal on computing,32(1):48–77, 2002.
  • P. Auer, N. Cesa-Bianchi, and P. Fischer. Finite-time analysis of the multi armed bandit problem. Machine learning, 47(2-3):235–256, 2002.

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A LoRa simulator with applied multi-armed bandit algorithms.

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