Efficient-spectrum management based on localisation of primary user position towards 5G
- Authors
- Gashema, Gaspard; Lee, Jae-Min; Kim, Dong-Seong
- Issue Date
- 15-Dec-2020
- Publisher
- INST ENGINEERING TECHNOLOGY-IET
- Keywords
- cognitive radio; Kalman filters; radio spectrum management; radio networks; 5G mobile communication; RSSI; interpolation; typical network; licensed system; unlicensed system; secondary users; unused frequency bands; licensed network; harmful interference; unused bands; KF; PUs position; received signal strength indicator scheme; localisation error prediction rate; system throughput; primary user position; broadband radio spectrum; current 4G technologies; efficient spectrum management; interweave cognitive radio networks; 5G
- Citation
- IET COMMUNICATIONS, v.14, no.20, pp 3567 - 3577
- Pages
- 11
- Journal Title
- IET COMMUNICATIONS
- Volume
- 14
- Number
- 20
- Start Page
- 3567
- End Page
- 3577
- URI
- https://scholarworks.bwise.kr/kumoh/handle/2020.sw.kumoh/25891
- DOI
- 10.1049/iet-com.2020.0284
- ISSN
- 1751-8628
1751-8636
- Abstract
- Recent emergent technologies with the advent of 5G use cases have made it imperative for high demands in broadband radio spectrum as compared to the current 4G technologies and other outdated ones. This study introduces an efficient spectrum management based on localisation of the primary user (PU) position in interweave cognitive radio networks (CRNs) towards 5G. In a typical network consisting of licensed system with PUs; and unlicensed system with secondary users (SUs), the SU opportunistically exploits the unused frequency bands of the licensed network provided there is no harmful interference to the PUs. Since the network is dynamic and the PUs are moving targets, the unused bands become unstable; hence, the SUs meet with limitations of detecting white spaces; finally resulting the interference. To this end, both Kriging interpolation and Kalman filter (KF) techniques for tracking and estimating the PUs position are proposed. The performance work was evaluated with respect to received signal strength indicator (RSSI) scheme. Both KF and Kriging interpolation outperformed RSSI. Moreover, the KF leads to the best performance compared to the other two as per localisation error prediction rate and system throughput; which makes it as the preferable technique to tackle mentioned challenges encountered by the SUs in such environment.
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