Paper Info
Title
A Novel Fair and Scalable Relay Control Scheme for Internet of Things in LoRa-Based Low-Power Wide-Area Networks
Abstract
This article proposes a novel fair and scalable relay control (FSRC) scheme for the Internet-of-Things (IoT) services in long range (LoRa)-based low-power wide-area networks. The proposed FSRC scheme promotes relay operation with low spreading factor (SF) to improve the success probability for distant end-devices (EDs) and the fairness of success probability for each SF region. To achieve this, a theoretical framework for designing the relay operation is analytically developed by considering a practical LoRaWAN MAC protocol as an analytical model. The proposed FSRC scheme encompasses a selective relay operation by considering both signal-to-noise ratio and signal-to-interference ratio and the receive signal strength indicator value for the location-unaware relay selection strategy. Using this model, a genetic algorithm-based relay control strategy is proposed to maximize both coverage probability and minimum success probability for all SF regions by controlling the relay parameters, such as source-relay region and source-relay ratio. Our numerical analysis validates the effectiveness of the proposed FSRC scheme under various parameters in terms of the minimum success probability of each SF region, coverage probability, and fairness. Specifically, we verify that the proposed FSRC scheme achieves a maximum of approximately 37% and 33% improvement of the minimum success probability and coverage probability, respectively, under practical LoRa PHY/MAC parameters, compared to the single-hop environment (without relay operation).
Year
DOI
Venue
2021
10.1109/JIOT.2020.3034185
IEEE Internet of Things Journal
Keywords
DocType
Volume
Cooperative relay,genetic algorithm,interference analysis,Internet of Things (IoT),long range (LoRa),low-power wide-area networks (LPWANs),pure ALOHA
Journal
8
Issue
ISSN
Citations 
7
2327-4662
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Sanghyun Lee100.68
Joohyung Lee2336.17
Hong-Shik Park311121.11
Jun Kyun Choi421.72