LoRaWAN simulation and analysis for performance enhancement of realistic networks

Citoni, Bruno (2022) LoRaWAN simulation and analysis for performance enhancement of realistic networks. PhD thesis, University of Glasgow.

Full text available as:
[img] PDF
Restricted to Repository staff only

Download (10MB)


The Internet of Things (IoT) is becoming an ubiquitous technology, with new devices, solutions and applications being developed at an ever-increasing rate.
Fundamental to the IoT revolution is the adoption of wireless protocols purposely designed to enable low-cost, long-range communication for numerous connected devices. Low Power Wide Area Networks (LPWANs) are wide area wireless telecommunication networks designed specifically for IoT applications. They allow for long-range communication at a low bit-rate among connected items, such as battery-powered sensors. However, with these benefits come also a number of drawbacks, including the limited data rate available and the reliance on low power channel access methods which can negatively impact performance in a highly dense network.
The purpose of the research contained in this work is to measure the performance in terms of Quality-of-Service (QoS), Packet Delivery Ratio (PDR) and scalability of one LPWAN in particular, Long Range Wide Area Network (LoRaWAN), as well as providing possible improvements that current and future network owners can put into practice. LoRaWAN simple channel access protocol, based on pure Additive Links On-line Hawaii Area (ALOHA) is intended to reduce cost, complexity, and energy consumption while increasing transmission range. However, it also severely limits the scalability of the technology, making it more prone to packet collision, despite LoRaWAN being particularly resilient to self-interference, thanks to the underlining, proprietary Long Range (LoRa) modulation. In this thesis, LoRaWAN technology is evaluated through both software simulation and experimental deployments, with the goal of gaining a deeper understanding of the technology to then create better models and better performing deployments. The innovations and novel results presented throughout will accelerate the pervasiveness of LPWAN networks such as LoRaWAN, and ultimately their effectivness.
Despite being developed in 2015, LoRa and LoRaWAN have both not been fully characterised, particularly in regard to large-scale behaviour. This is partly due to the low feasibility of deploying vast networks. To address this, the first recorded instance of anurban digital twin of 20 devices LoRaWAN network was deployed and analysed.
The available simulation models, despite being successfully used in various research studies, are also not fully complete, and a deeper understanding of the technology is required to fix some remaining open issues.
To give additional insight into their operation as well as practical improvements that can be carried out to maximise performance, both from a consumer and an industrial standpoint, existing LoRa and LoRaWAN modules for the network simulator NS-3 are enhanced and used throughout the work presented. Scalability and Quality-of-Service improvements are also presented, based on the knowledge gaps found in current LoRaWAN research and the results of the simulations performed. In particular, improvements on PDR up to 10% are reported using novel techniques of downlink independent optimisation, and new insight on the positioning of gateways to achieve maximum scalability in a two-gateways network are also highlighted.

Item Type: Thesis (PhD)
Qualification Level: Doctoral
Subjects: T Technology > T Technology (General)
Colleges/Schools: College of Science and Engineering > School of Engineering
Funder's Name: Engineering and Physical Sciences Research Council (EPSRC)
Supervisor's Name: Hussain, Dr. Sajjad and Abbasi, Dr. Qammer
Date of Award: 2022
Depositing User: Theses Team
Unique ID: glathesis:2022-83289
Copyright: Copyright of this thesis is held by the author.
Date Deposited: 01 Dec 2022 15:14
Last Modified: 13 Dec 2022 12:21
Thesis DOI: 10.5525/gla.thesis.83289
URI: http://theses.gla.ac.uk/id/eprint/83289
Related URLs:

Actions (login required)

View Item View Item


Downloads per month over past year