Experimental Assessment of Common Crucial Factors That Affect LoRaWAN Performance on Suburban and Rural Area Deployments.

LPWAN LoRaWAN clustering network administration network planning performance scalability

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
24 Jan 2023
Historique:
received: 20 12 2022
revised: 13 01 2023
accepted: 18 01 2023
entrez: 11 2 2023
pubmed: 12 2 2023
medline: 12 2 2023
Statut: epublish

Résumé

LoRaWAN networks might be a technology that could facilitate extreme energy-efficient operation while offering great capacity for suburban and rural area deployment, but this can be a challenging task for a network administrator. Constraints that deform the trade-off triangle of coverage, scalability and energy efficiency need to be overcome. The scope of this study is to review the limitations of the LoRaWAN protocol in order to summarize and assess the crucial factors that affect communication performance, related to data rate allocation, bidirectional traffic and radio spectrum utilization. Based on the literature, these factors correspond mostly to configurable payload transmission parameters, including transmission interval, data rate allocation, requirement for acknowledgements and retransmission. In this work, with simulation experiments, we find that collision occurrences greatly affect channel occupancy. In particular, it was evaluated that collision occurrence is increasingly affected by transmission intervals, which have the most significant negative impact on packet delivery rate (PDR). We then validated that clustering of end nodes in the vicinity of a gateway, taking into account distance and transmission settings, can improve network scalability. This can assure distribution of the total transmission time to end nodes with respect to application-related QoS requirements. Following this clustering approach, we achieved a PDR greater than 0.90 in a simulation setting with 6000 end nodes in a 10 km coverage.

Identifiants

pubmed: 36772356
pii: s23031316
doi: 10.3390/s23031316
pmc: PMC9921199
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : General Secretariat for Research and Technology
ID : 2018ΣΕ01300000

Références

Sensors (Basel). 2020 Jul 21;20(14):
pubmed: 32708173
Sensors (Basel). 2020 Aug 04;20(15):
pubmed: 32759657
Sensors (Basel). 2022 Mar 05;22(5):
pubmed: 35271189

Auteurs

Markos Fragkopoulos (M)

Department of Electrical and Computer Engineering, Hellenic Mediterranean University, 71004 Heraklion, Greece.

Spyridon Panagiotakis (S)

Department of Electrical and Computer Engineering, Hellenic Mediterranean University, 71004 Heraklion, Greece.

Michail Kostakis (M)

Department of Electrical and Computer Engineering, Hellenic Mediterranean University, 71004 Heraklion, Greece.

Evangelos K Markakis (EK)

Department of Electrical and Computer Engineering, Hellenic Mediterranean University, 71004 Heraklion, Greece.

Nikolaos Astyrakakis (N)

Department of Electrical and Computer Engineering, Hellenic Mediterranean University, 71004 Heraklion, Greece.

Athanasios Malamos (A)

Department of Electrical and Computer Engineering, Hellenic Mediterranean University, 71004 Heraklion, Greece.

Classifications MeSH