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Title: | Scalability analysis of LoRa network for SNR-based SF allocation scheme |
Authors: | Saluja, D. Singh, R. Baghel, L.K. Kumar, S. |
Keywords: | Long range wide area network (LoRaWAN) LoRa network Scalability Spreading factor (SF) allocation Stochastic geometry |
Issue Date: | 22-Aug-2022 |
Abstract: | Over the past few years, we have witnessed an explosive increase in the number of long range wide area network (LoRaWAN) devices, primarily because LoRaWAN offers attractive features such as long-range, low-power, and low-cost communications. However, the scalability of LoRaWAN is a major concern, which in particular depends on spreading factor (SF) allocation schemes. Primarily, SFs are assigned based on distance from the gateway, using equal-interval-based (EIB) and equal-area-based (EAB) SF allocation schemes. In this article, we have proposed an SNR-based SF allocation scheme to improve the scalability of LoRaWAN. We have introduced two different algorithms for the proposed scheme. Using stochastic-geometry, an analytical framework is developed for both the algorithms, and the expressions are derived for the packet success probability (PSP) under the co-SF interference scenario. In addition, the impact of an inter-SF interference on the PSP performance is analyzed by simulations. The proposed algorithms are compared with the EIB and EAB SF allocation schemes, and it is shown that the proposed algorithms perform better than the other two schemes. We have also analyzed the impact of end device density, packet size, and cell-radius on the LoRaWAN scalability. Moreover, we have performed real-time experiments to prove the applicability of the presented work in practical scenarios. |
URI: | http://localhost:8080/xmlui/handle/123456789/3859 |
Appears in Collections: | Year-2021 |
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