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Leveraging on the Cognitive Radio Channel Aggregation Strategy for Next Generation Utility Networks

Authors :
Esenogho Ebenezer
Theo. G. Swart
Thokozani Shongwe
Source :
Energies, Vol 12, Iss 14, p 2753 (2019)
Publication Year :
2019
Publisher :
MDPI AG, 2019.

Abstract

Integrating cognitive radio into the current power grid is designed to enable smart communication and decisions within the grid. Communication within the grid is not feasible without channel(s) and most studies have emphasized the use of cellular spectrum. This study proposes a strategy that enables the use of television white space (TVWS) within the grid. To be specific, we propose using a next-generation utility network (Next-GUN), which leverages on the cognitive radio (CR) channel aggregation capability. This strategy enables the aggregation of idle TVWS into a usable channel, thus making the Next-GUN different from the traditional power network. Next-GUN differs in terms of security, reliability, self-awareness, and cross-layer compatibility to the interface, and conveys different traffic classes, thereby making it a hybrid system. It has no dedicated channel assigned to it, and hence, utilizes the idle TVWS opportunistically to transmit data. The proposed scheme was modelled as a Markovian process and analyzed using a continuous time Markov chain (CTMC). Extensive system simulations were performed to evaluate this proposed model and the corresponding comparison with the literature was done to see the improvement. The result of our comparisons shows that when channels are aggregated, more data/information are transmitted. In addition, the use of cognitive radios on a power network enables smart transaction because idle TVWS is utilized instead of congesting the GSM spectrum. Lastly, the power utility establishment can save the cost of paying for a licensed spectrum.

Details

Language :
English
ISSN :
19961073
Volume :
12
Issue :
14
Database :
Directory of Open Access Journals
Journal :
Energies
Publication Type :
Academic Journal
Accession number :
edsdoj.f6aed5652644b679e7c59ecbb447f2c
Document Type :
article
Full Text :
https://doi.org/10.3390/en12142753