Cognitive Radio in Low Power Wide Area Network for IoT Applications : Recent Approaches, Benefits and Challenges
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
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Detail(s)
Original language | English |
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Pages (from-to) | 7489-7498 |
Journal / Publication | IEEE Transactions on Industrial Informatics |
Volume | 16 |
Issue number | 12 |
Online published | 28 Nov 2019 |
Publication status | Published - Dec 2020 |
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Abstract
Some recent survey statistics suggest that low power wide area networks (LPWANs) are fast becoming the most prevalent communication platform used in many applications of the Internet of Things (IoT). However, because most LPWANs are generally deployed in the presently congested industrial, scientific, and medical bands, they are invariably plagued by problems associated with spectral congestion, such as increased interference, reduced data rates, and spectra inefficiency. These problems are solvable by integrating cognitive radio (CR) technologies in LPWAN (termed CR-LPWAN), for which some pioneering solutions now exist in the literature. Consequently, this article takes an early look at some of these pioneering efforts pertaining to the development of CR-LPWAN systems. We discuss a general network architecture and a physical layer front-end model suitable for CR-LPWAN systems. Then, some notable state-of-the-art approaches for CR-LPWAN systems are discussed. Potential advantages of CR-LPWAN systems for IoT-based applications are also presented, and this article closes with a few research challenges and future research directions in this regard. This article aims to serve as a starting point for most budding researchers who may be interested in the development of effective and efficient CR-LPWAN systems for the enhancement of different IoT-based applications.
Research Area(s)
- Standards, Internet of Things, Cognitive radio, White spaces, Wireless sensor networks, Informatics, Wide area networks, industrial, low power wide area network (LPWAN), survey, ALGORITHMS
Citation Format(s)
Cognitive Radio in Low Power Wide Area Network for IoT Applications: Recent Approaches, Benefits and Challenges. / Onumanyi, Adeiza J.; Abu-Mahfouz, Adnan M.; Hancke, Gerhard P.
In: IEEE Transactions on Industrial Informatics, Vol. 16, No. 12, 12.2020, p. 7489-7498.
In: IEEE Transactions on Industrial Informatics, Vol. 16, No. 12, 12.2020, p. 7489-7498.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review