Guimarães, D.A., Pereira, E.J.T., Alberti, A.M. orcid.org/0000-0002-0947-8575 et al. (1 more author) (2021) Design Guidelines for Database-Driven Internet of Things-Enabled Dynamic Spectrum Access. Sensors, 21 (9). 3194. ISSN: 1424-8220
Abstract
The radio-frequency spectrum shortage, which is primarily caused by the fixed allocation policy, is one of the main bottlenecks to the deployment of existing wireless communication networks, and to the development of new ones. The dynamic spectrum access policy is foreseen as the solution to this problem, since it allows shared spectrum usage by primary licensed and secondary unlicensed networks. In order to turn this policy into reality, the secondary network must be capable of acquiring reliable, real-time information on available bands within the service area, which can be achieved by means of spectrum sensing, spectrum occupancy databases, or a combination of them. This Review presents guidelines related to the design of a framework that can be adopted to foster dynamic spectrum access policies. The framework applies special-purpose Internet of Things (IoT) devices that perform spectrum sensing, subsequently feeding a spectrum occupancy database, which in turn will be used by the secondary network to gather information on location-dependent spectrum availability. The guidelines address technological enablers capable of making the framework feasible, reliable and secure.
Metadata
| Item Type: | Article |
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| Authors/Creators: |
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| Copyright, Publisher and Additional Information: | © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
| Keywords: | blockchain; cognitive radio; distributed ledger technology; dynamic spectrum access; Internet of things; spectrum sensing |
| Dates: |
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| Institution: | The University of Leeds |
| Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
| Date Deposited: | 19 Jan 2026 16:23 |
| Last Modified: | 19 Jan 2026 16:23 |
| Status: | Published |
| Publisher: | MDPI |
| Identification Number: | 10.3390/s21093194 |
| Related URLs: | |
| Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:236391 |

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