Analyzing LoRa long-range, low-power, wide-area networks using stochastic geometry - Inria - Institut national de recherche en sciences et technologies du numérique
Communication Dans Un Congrès Année : 2019

Analyzing LoRa long-range, low-power, wide-area networks using stochastic geometry

Résumé

In this paper we present a simple, stochastic-geometric model of a wireless access network exploiting the LoRA (Long Range) protocol, which is a non-expensive technology allowing for long-range, single-hop connectivity for the Internet of Things. We assume a space-time Poisson model of packets transmitted by LoRA nodes to a fixed base station. Following previous studies of the impact of interference, we assume that a given packet is successfully received when no interfering packet arrives with similar power before the given packet payload phase. This is as a consequence of LoRa using different transmission rates for different link budgets (transmissions with smaller received powers use larger spreading factors) and LoRa intra-technology interference treatment. Using our model, we study the scaling of the packet reception probabilities per link budget as a function of the spatial density of nodes and their rate of transmissions. We consider both the parameter values recommended by the LoRa provider, as well as proposing LoRa tuning to improve the equality of performance for all link budgets. We also consider spatially non-homogeneous distributions of LoRa nodes. We show also how a fair comparison to non-slotted Aloha can be made within the same framework.

Dates et versions

hal-01958939 , version 1 (18-12-2018)

Identifiants

Citer

Bartłomiej Błaszczyszyn, Paul Mühlethaler. Analyzing LoRa long-range, low-power, wide-area networks using stochastic geometry. VALUETOOLS 2019 - 12th EAI International Conference on Performance Evaluation Methodologies and Tools, ACM, Mar 2019, Palma de Mallorca, Spain. ⟨10.1145/3306309.3306327⟩. ⟨hal-01958939⟩
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