Energy Efficiency in LoRa networks - An Approach from Stochastic Geometry

Lam-Thanh Tu (1) , Abbas Bradai (1) , Yannis Pousset (1)

1 XLIM - XLIM

In this letter, the closed-form expression of the energy efficiency (EE) in LoRa networks is formulated and derived based on tools from stochastic geometry. In addition, the insights of EE respect to some essential parameters, i.e., the density of EDs and the transmit power are proven based on the rigorous mathematical frameworks. Our findings show that, the EE monotonically decreases respect to the average number of end-devices (EDs) and a pseudo-concave function respect to the transmit power. Furthermore, the asymptotic framework of EE when the average number of EDs approaches zero is also derived. Finally, Monte Carlo simulations are provided to verify the correctness of our framework.

Mots clés: Index Terms-LoRa; Energy Efficiency; Stochastic Geometry; System-Level Analysis

Domaines: Modélisation et simulation

Lam-Thanh Tu, Abbas Bradai, Yannis Pousset. Energy Efficiency in LoRa networks - An Approach from Stochastic Geometry. 2020. ⟨hal-02977258v1⟩