Database-assisted spectrum prediction in 5g networks and beyond: A review and future challenges

Marko Höyhtyä, Aarne Mämmelä, Alessandro Chiumento, Sofie Pollin, Martti Forsell, Danijela Cabric

    Research output: Contribution to journalArticleScientificpeer-review

    22 Citations (Scopus)

    Abstract

    This article surveys the state of the art in spectrum prediction and learning, summarizes applications, techniques, main metrics, computational complexity, and provides practical examples. We focus on a cellular case study and define required improvements to database-assisted spectrum sharing. The use of history information and predictive spectrum modeling at different time scales provides valuable information to regulators, operators, and users of dynamic spectrum access networks. Prediction enables dynamic spectrum sharing systems to operate proactively, and consequently improves the performance in terms of reducing delays and interference among coexisting systems. Current database-assisted spectrum sharing concepts are in fact too static for many applications. Our numerical results on local-aware predictive spectrum allocation show the advantage of predictive operation in a vehicle-to-everything (V2X) scenario.

    Original languageEnglish
    Article number8792447
    Pages (from-to)34 - 45
    Number of pages12
    JournalIEEE Circuits and Systems Magazine
    Volume19
    Issue number3
    DOIs
    Publication statusPublished - 2019
    MoE publication typeA1 Journal article-refereed

    Funding

    Discussions with Dr. Esa Piri on mobility management problems and Mr. Marko Palola on CBRS system implementation problems are acknowledged. The work was supported by the CORNET and the WIVE projects, partly funded by Business Finland. Danijela Cabric is Professor in the Elec-trical and Computer Engineering Depart-ment at the University of California, Los Angeles. Her research interests include novel radio architectures, signal process-ing, communications, machine learning and networking techniques for cognitive radio, 5G and massive MIMO systems. Dr. Cabric received the Samueli Fellowship in 2008, the Okawa Foundation Research Grant in 2009, Hellman Fellowship in 2012 and the National Science Foundation Faculty Early Career Development (CAREER) Award in 2012. She served as an Associate Editor in IEEE Journal on Selected Areas in Communications (Cognitive Radio series) and IEEE Communications Letters, and TPC Co-Chair of 8th International Conference on Cognitive Radio Oriented Wireless Networks (CROWNCOM) 2013. She is now an Associate Editor of IEEE Transactions of Cognitive Communications and Networking, IEEE Transactions on Wireless Communications and IEEE Transactions on Mobile Computing. She is a Senior Member of IEEE and ComSoc Distinguished Lecturer.

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