Please use this identifier to cite or link to this item: https://repository.sustech.edu/handle/123456789/22796
Title: Modeling and Evaluation of LoRa and Sigfox Low Power Wide Area Networks for Internet of Things
Other Titles: نمذجة وتقييم شبكات لورا وسيق فوكس الواسعة متدنية القدرة لأنترنت الأشياء
Authors: Elamin, Esra Bashir Abbas
Supervisor, - Niemah Izzeldin Mohamed Osman
Keywords: Electronics Engineering
Communication Engineering
Modeling and Evaluation
LoRa and Sigfox Low
Power Wide Area
Networks for Internet
Issue Date: 10-Nov-2019
Publisher: Sudan University of Science and Technology
Citation: Elamin, Esra Bashir Abbas . Modeling and Evaluation of LoRa and Sigfox Low Power Wide Area Networks for Internet of Things / Esra Bashir Abbas Elamin ; Niemah Izzeldin Mohamed Osman .- Khartoum: Sudan University of Science and Technology, College of Engineering, 2018 .- 54p. :ill. ;28cm .- M.Sc.
Abstract: During this decade, there is a huge expansion in the number of low-power Internet connected devices. The Low Power Wide Area Network (LPWAN); because of its low-cost communication ability and long-range, is considered as the future wireless communication standard for Internet of Things (IoT). Although IoT is gaining more popularity, it is hard to identify the suitability of LPWAN technologies for those IoT devices. In this thesis a simulation modeling had been developed focusing on LoRa and Sigfox to evaluate each individual LPWAN technology. The influence of the number of devices on LoRa and Sigfox performance had been evaluated by measuring collision, packet error rate and spectrum under 500 and 1000 number of IoT devices and bandwidths (125,250 and 500KHz )for LoRa and 200 KHz for Sigfox. The results show that Sigfox has less collisions and packet error rate compared to LoRa. Also in general, by increasing the number of devices leads to increasing collision and packet error rate, the higher the bandwidth the less collision and more available slots.
Description: Thesis
URI: http://repository.sustech.edu/handle/123456789/22796
Appears in Collections:Masters Dissertations : Engineering

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