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        Chapter Spinel Ferrite Nanoparticles: Correlation of Structure and Magnetism

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        Author(s)
        Reznickova, Alice
        Vejpravova, Jana
        Kubickova, Simona
        Pacakova, Barbara
        Language
        English
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        Abstract
        Filter bank multi‐carrier (FBMC) modulation, as a potential candidate for physical data communication in the fifth generation (5G) wireless networks, has been widely investigated. This chapter focuses on the spectral efficiency analysis of FBMC‐based cognitive radio (CR) systems, and spectral efficiency comparison is conducted with another three types of multi‐carrier modulations: orthogonal frequency division multiplexing (OFDM), generalized frequency division multiplexing (GFDM), and universal‐filtered multi‐carrier (UFMC). In order to well evaluate and compare the spectral efficiency, we propose two resource allocation (RA) algorithms for single‐cell and two‐cell CR systems, respectively. In the single‐cell system, the RA algorithm is divided into two sequential steps, which incorporate subcarrier assignment and power allocation. In the two‐cell system, a noncooperative game is formulated and the multiple access channel (MAC) technique assists to solve the RA problem. The channel state information (CSI) between CR users and licensed users cannot be precisely known in practice, and thus, an estimated CSI is considered by defining a prescribed outage probability of licensed systems. Numerical results show that FBMC can achieve the highest channel capacity compared with another three waveforms.
        URI
        https://library.oapen.org/handle/20.500.12657/49194
        Keywords
        filter bank multi‐carrier, spectral efficiency, resource allocation, cognitive radio, 5G networks
        DOI
        10.5772/66074
        Publisher
        InTechOpen
        Publisher website
        https://www.intechopen.com/
        Publication date and place
        2017
        Classification
        WAP (wireless) technology
        Rights
        https://creativecommons.org/licenses/by/3.0/
        • Imported or submitted locally

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        License

        • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

        Credits

        • logo EU
        • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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