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    Energy-efficient GCSA medium access protocol for infrastructure-based cognitive radio networks

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    Authors
    Syed, Tazeen Shabana
    Safdar, Ghazanfar Ali
    Affiliation
    University of Bedfordshire
    Issue Date
    2019-06-05
    Subjects
    cognitive radio networks
    
    Metadata
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    Abstract
    The major challenge encountered by battery-driven wireless local area networking devices is to conserve their energy for prolonged operation. This paper presents an energy-efficient medium access mechanism called group control slot allocation (GCSA) protocol for cognitive radio (CR) networks. GCSA utilizes the group priority allocation algorithm to allocate stations (STAs) into groups; subsequently STAs that have traffic buffered in an access point are assigned to a higher priority group. A management frame, namely group monitoring pointer, optimizes the sleep-awake cycle of the STAs by allocating transmission opportunities to groups based on their priority. GCSA employs publisher-subscriber and point-to-point messaging models for communication between the base station and STAs, respectively. Performance analysis of GCSA demonstrates that increasing the number of STAs which enter into sleep mode augments the percentage of energy saved. The overall system-level results show that energy saved is around 20% higher for GCSA than the IEEE 802.11e standard hybrid coordination function power-saving mode. Since GCSA benefits from history-assisted-led spectrum sensing, the paper also presents the relationship of the local storage of CRs with respect to history and suggests a hybrid approach as best option to keep a balance between the sensed data and its sharing with analytical engine database for history enrichment leading toward improved energy efficiency.
    Citation
    Syed TS, Safdar GA (2020) 'Energy-efficient GCSA medium access protocol for infrastructure-based cognitive radio networks', IEEE Systems Journal, 14 (1), pp.288-297.
    Publisher
    IEEE
    Journal
    IEEE Systems Journal
    URI
    http://hdl.handle.net/10547/624067
    DOI
    10.1109/JSYST.2019.2917836
    Additional Links
    https://ieeexplore.ieee.org/document/8731676
    Type
    Article
    Language
    en
    ISSN
    1932-8184
    EISSN
    1937-9234
    ae974a485f413a2113503eed53cd6c53
    10.1109/JSYST.2019.2917836
    Scopus Count
    Collections
    Computing

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