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Spectrum Sensing Challenges: Blind Sensing and Sensing Optimization
University of Gävle, Faculty of Engineering and Sustainable Development, Department of Electronics, Mathematics and Natural Sciences, Electronics. KTH, Stockholm, Sweden; University of Agder, Kristiansand, Norway.ORCID iD: 0000-0003-3860-5964
KTH, Stockholm, Sweden.
University of Gävle, Faculty of Engineering and Sustainable Development, Department of Electronics, Mathematics and Natural Sciences, Electronics.
University of Gävle, Faculty of Engineering and Sustainable Development, Department of Electronics, Mathematics and Natural Sciences, Electronics.ORCID iD: 0000-0001-5429-7223
2016 (English)In: IEEE Instrumentation & Measurement Magazine, ISSN 1094-6969, E-ISSN 1941-0123, Vol. 19, no 2, p. 44-52Article in journal (Refereed) Published
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Abstract [en]

By any measure, wireless communications is one of the most evolving fields in engineering. This, in return, has imposed many challenges, especially in handling the hunger for higher data rates in the next generation wireless networks. Among these challenges is how to provide the needed resources in terms of the electromagnetic radio spectrum for these networks. In this regard, cognitive radio (CR) based on dynamic spectrum access (DSA) has been attracting huge attention as a promising solution for more efficient utilization of the available radio spectrum. DSA is based on finding and opportunistically accessing the free-of-use portions of spectrum. To facilitate DSA, spectrum sensing can be used. However, spectrum sensing faces many challenges in different aspects. Such aspects include blind sensing and sensing optimization, which are both to a great extent measurement challenges. We discuss different contributions in addressing these two challenges in this article.

Place, publisher, year, edition, pages
2016. Vol. 19, no 2, p. 44-52
Keywords [en]
cognitive radio, next generation networks, radio communication, radio systems, wireless networks, next generation wireless network, radio spectra
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:hig:diva-21563DOI: 10.1109/MIM.2016.7462794ISI: 000375571400012Scopus ID: 2-s2.0-84969534000OAI: oai:DiVA.org:hig-21563DiVA, id: diva2:935086
Available from: 2016-06-10 Created: 2016-06-10 Last updated: 2023-02-17Bibliographically approved

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Hamid, MohamedVan Moer, WendyBjörsell, Niclas

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