Improving the Scalability of LoRa Networks Through Dynamical Parameter Set Selection

Cai, Qingsong; Lin, Jia Wei

doi:10.1007/978-981-15-1785-3_1

Cited by 2 publications

(1 citation statement)

References 21 publications

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“…The majority of the studies are based on optimal resource (SF) allocation. In [15], [12], [31], [11], this kind of approach has been adapted to enhance the capacity and overall system performance.…”

Section: Related Workmentioning

confidence: 99%

Designing LoRaWAN Network For Unbiased Communication Between Nodes and Gateway

Maurya

Singh

Kherani

2021

Preprint

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Proper cell designing is required to achieve a target system performance in Long Range Wide Area Network (LoRaWAN). This paper addresses a suitable selection of network designing parameters problem, such as the dimension of different spreading factors’ annuli (zones or SF boundaries) in a LoRaWAN cell. We propose a mathematical framework for designing the LoRaWAN network. The main objective is to ensure that distributed end devices in the network can have the same success probability, irrespective of the spreading factor usage and their locations, unlike Equal Area Based (EAB) based network. We further enhance the performance of the network based on the proposed dimensions by adopting the k-tolerance algorithm. When the network follows the proposed dimensions, simulation results show an improvement in overall success probability over the traditional EAB scheme. In the later part of the paper, we address urbanization issues that degrade the system performance. In our approach to recoup the degradation in the system performance, we implement k−tolerance algorithm in the network.

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