Multi-class random access wireless network: General results and performance analysis of LoRaWAN

doi:10.1016/j.adhoc.2022.102946

Ad Hoc Networks

Volume 135, 1 October 2022, 102946

https://doi.org/10.1016/j.adhoc.2022.102946 Get rights and content

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Abstract

This paper presents new analytical results for evaluating the ALOHA-like multi-class random access wireless network’s performance. The proposed model is motivated by the growth of low-power wireless networks that employ random access protocols. In particular, we compare our analytical formulation with system-level simulations of Long Range (LoRa) technology. We show that the proposed formulation provides an accurate approximation of LoRaWAN performance capturing its main trade-offs. The main contributions are (i) an extensive analysis of the impact of different LoRa spreading factors (SFs) allocation strategies, including area intersection among SFs, which is little explored in the literature and represents the optimal approach under some conditions; and (ii) the optimal proportion of users that maximizes the network throughput for each class and for each allocation strategy considered in the paper.

Keywords

LoRa

Spreading factor allocation

Multi-class wireless network

Data availability

No data was used for the research described in the article.

Cited by (0)

Francisco Helder C. dos Santos Filho is Adjunct Professor of Federal University of Ceará. He received B.S. degree in electrical engineering from the Federal University of Ceará (UFC - 2001) with a master’s degree (2005) and Ph.D. (2021) in Telecommunications Engineering from FEEC - University of Campinas (Unicamp). Worked for 12 years with R&D projects in companies such as Lucent, Nokia Siemens Networks, Datacom, and CPqD, which was the firmware leader for implementing wired and wireless network equipment. Main areas of interest: computer network, IoT radio interfaces, wireless communications, wireless sensor network (WSN), communications protocols, embedded systems, embedded system programming, and Real-Time OS.

Plínio Santini Dester received the B.S. degree in engineering from the École Polytechnique, France, and the B.S. degree in electrical engineering from the University of Campinas, Brazil, following a double degree program, which also conferred the master’s degree in 2017. He is currently pursuing the Ph.D. degree in electrical engineering with the University of Campinas (UNICAMP), Brazil. During under graduation, he worked as an Intern with Orange Labs, France, the National Institute for Research in Computer Science and Automation (INRIA), France, the National Center for Research in Energy and Materials (CNPEM), Brazil, and UNICAMP. His research interests include wireless communications and networking, with a focus on theoretical analysis of the performance through stochastic geometry and queueing theory.

Pedro H.J. Nardelli [M’07, SM’19] received the B.S. and M.Sc. degrees in electrical engineering from the State University of Campinas, Brazil, in 2006 and 2008, respectively. In 2013, he received his doctoral degree from University of Oulu, Finland, and State University of Campinas following a dual degree agreement. He is currently Associate Professor (tenure track) in IoT in Energy Systems at LUT University, Finland, and holds a position of Academy of Finland Research Fellow with a project called Building the Energy Internet as a large-scale IoT-based cyber–physical system that manages the energy inventory of distribution grids as discretized packets via machine-type communications (EnergyNet). He leads the Cyber-Physical Systems Group at LUT, and is Project Coordinator of the CHIST-ERA European consortium Framework for the Identification of Rare Events via Machine Learning and IoT Networks (FIREMAN) and of the project Swarming Technology for Reliable and Energy-aware Aerial Missions (STREAM) supported by Jane and Aatos Erkko Foundation. He is also Docentat University of Oulu in the topic of “communications strategies and information processing in energy systems”. His research focuses on wireless communications particularly applied in industrial automation and energy systems. He received a best paper award of IEEE PES Innovative Smart Grid Technologies Latin America 2019 in the track “Big Data and Internet of Things”. He is also IEEE Senior Member. More information: https://sites.google.com/view/nardelli/.

Elvis M.G. Stancanelli received the B.S. degree from the State University of Londrina (UEL), Brazil, in 2002, and the M.Sc. degree from the University of São Paulo (USP), Brazil, in 2004, both in electrical engineering. In 2012 he received the doctoral degree from the Federal University of Ceará (UFC), Brazil, in teleinformatics engineering. From 2004 to 2013, he was with Wireless Telecommunications Research Group (GTEL), Brazil, as a research engineer involved with investigaionts on mobile communications; in autumn 2009, he was a visiting researcher with Ericsson Research, Sweden. Since 2013, he is adjunct professor at UFC. His research interests include wireless and mobile communications, IoT radio interfaces, digital signal processing, computer simulation methods, and machine learning.

Paulo Cardieri received the B.S. degree from the Mauá School of Engineering, Brazil, in 1987, the M.Sc. degree from the University of Campinas (UNICAMP), Campinas, Brazil, in 1994, and the Ph.D. degree from the Virginia Polytechnic Institute and State University, Blacksburg, VA, USA, all in electrical engineering. He is currently an Associate Professor with the School of Electrical and Computer Engineering, UNICAMP. Prior to joining the Faculty of UNICAMP, he was with the CPqD Foundation, Campinas, where he was involved with several research projects on communications, including satellite and wireless communications. From November 1991 to August 1992, he was a Visiting Researcher with the Centro Studi e Laboratori Telecomunicazioni, Turin, Italy. His current research interests include wireless ad hoc networks, sensor networks, and modeling of communication systems.

Dick Carrillo Melgarejo received the B.Eng. degree (Hons.) in electronics and electrical engineering from San Marcos National University, Lima, Perú, and the M.Sc.degree in electrical engineering from Pontifical Catholic University of Rio de Janeiro, Rio deJaneiro, Brazil, in 2004 and 2008, respectively. Between 2008 and 2010, he contributed to WIMAX (IEEE 802.16m) standardization. From 2010 to 2018, he worked with the design and implementation of cognitive radio networks and projects based on 3GPPtechnologies. Since 2018 he is a researcher at Lappeenranta–Lahti University of Technology, where he is also pursuing the Ph.D degree in electrical engineering. His research interests are mobile technologies beyond5G, energy harvesting, intelligent meta-surfaces, Cell-free mMIMO, and RAN Slicing.

Hirley Alves is Assistant Professor and Head of the Machine-type Wireless Communications Group at the 6G Flagship, Centre for Wireless Communications, University of Oulu. He is actively working on massive connectivity and ultra-reliable low latency communications for future wireless networks, 5GB and 6G, full-duplex communications, and physical-layer security. He leads the URLLC activities for the 6G Flagship Program. He has received several awards and has been the organizer, chair, TPC and tutorial lecturer for several renowned international conferences. He is the General Chair of the ISWCS’2019 and the General Co-Chair of the 1st 6G Summit, Levi 2019, and ISWCS 2021.

¹: This paper is partly supported by Foundation for Research Support of the State of São Paulo, Brazil (Grant No. 2017/21347-0). This work as also financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001.

²: Senior Member, IEEE.

³: This paper is partly supported by Academy of Finland via: (a) ee-IoT n.319009, (b) FIREMAN consortium CHIST-ERA-17-BDSI-003/n.326270, and (c) EnergyNet Fellowship n.321265/n.328869.

⁴: Member, IEEE.

⁵: This paper is partly supported by 6G Flagship (Grant n.318927), and ee-IoT ( n.319008) and FIREMAN consortium ( CHIST-ERA-17-BDSI-003/n.24303093).