Optimal Bandwidth Allocation for Multicast-Cache-Aided on-Demand Streaming in Wireless Networks

    Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussaConference article in proceedingsScientificvertaisarvioitu

    1 Sitaatiot (Scopus)
    72 Lataukset (Pure)

    Abstrakti

    We consider a hybrid delivery scheme for streaming content, combining cache-enabled Orthogonal Multipoint Multicast (OMPMC) and on-demand Single-Point Unicast (SPUC) transmissions for heterogeneous networks. The OMPMC service transmits cached files through the whole network to interested users, and users not being satisfied by this service are assigned to the SPUC service to be individually served. The SPUC fetches the requested files from the core network and unicasts them to UEs using cellular beamforming transmissions. We optimize the delivery scheme to minimize the average resource consumption in the network. We formulate a constrained optimization problem over the cache placement and resource allocation of the OMPMC component, as well as the multi-user beamforming scheme of the SPUC component. We apply a path-following method to find the optimal traffic offloading solution. The solutions portray a contrast between the total amount of consumed resources and service outage probability. Simulation results show that the hybrid scheme provides a better tradeoff between the amount of network-wide consumed resources and the service outage probability, as compared to schemes from the literature.
    AlkuperäiskieliEnglanti
    OtsikkoGLOBECOM 2022 - 2022 IEEE Global Communications Conference
    KustantajaIEEE
    Sivut1936-1941
    Sivumäärä6
    ISBN (elektroninen)978-1-6654-3540-6
    DOI - pysyväislinkit
    TilaJulkaistu - 2022
    OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
    TapahtumaIEEE Global Communications Conference - Rio de Janeiro, Brasilia
    Kesto: 4 jouluk. 20228 jouluk. 2022

    Conference

    ConferenceIEEE Global Communications Conference
    LyhennettäGLOBECOM
    Maa/AlueBrasilia
    KaupunkiRio de Janeiro
    Ajanjakso04/12/202208/12/2022

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