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Scalability analysis of LoRa network using multiple gateways

R Shunmugam, Thivillan (2022) Scalability analysis of LoRa network using multiple gateways. Project Report. Universiti Teknikal Malaysia Melaka, Melaka, Malaysia. (Submitted)

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Abstract

LoRa is a long-range low-power network technology that is distinct and impressive due to its low power consumption and low-cost system architecture. LoRa is a wireless technology that provides secure data transmission for M2M and IoT applications. While applications of LoRa are increasing at tremendous pace, little attention has been paid to the scalability and performance analysis of such networks. It is very important to analyze how well these technologies will scale as the number of connected devices grows in the future. Numerous endnodes transmits the data signal to a single gateway and this causes traffic overload. In this project, firstly the traffic overload analysis of a single LoRa gateway that receives signal from numerous end-nodes is performed. Then, this project propose to scale LoRa network by using multiple gateways as receivers to reduce the data signal overload by the single gateway. Finally, LoRa performance based on the collision behavior of the data signal from end-node to the gateway is analyzed using Matlab platform. The results shows that the received values become stable at the multiple gateways but were fluctuating at the single gateway. Thus, the traffic collision is present when the number of end nodes increases and by adding another receiver to the gateway, the traffic collision reduces. This project will be extremely beneficial because a system designer can use the LoRa information and specifications as a foundation for future projects. Furthermore, because the LoRa parameter has been determined, this project will facilitate the development of IoT-related products.

Item Type: Final Year Project (Project Report)
Uncontrolled Keywords: Gateway, Traffic Overload, Signal, Gateways, Applications, Collision, Scalability, Analysis
Divisions: Library > Final Year Project > FKEKK
Depositing User: Mr Eiisaa Ahyead
Date Deposited: 24 Oct 2023 08:15
Last Modified: 24 Oct 2023 08:15
URI: http://digitalcollection.utem.edu.my/id/eprint/27945

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