Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/81779
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dc.contributorDepartment of Computing-
dc.creatorYang, JCen_US
dc.creatorLuo, JTen_US
dc.creatorWang, JXen_US
dc.creatorGuo, Sen_US
dc.date.accessioned2020-02-10T12:29:08Z-
dc.date.available2020-02-10T12:29:08Z-
dc.identifier.issn2169-3536en_US
dc.identifier.urihttp://hdl.handle.net/10397/81779-
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.rightsThis work is licensed under a Creative Commons Attribution 4.0 License. For more information, see http://creativecommons.org/licenses/by/4.0/en_US
dc.rightsThe following publication J. Yang, J. Luo, J. Wang and S. Guo, "CMU-VP: Cooperative Multicast and Unicast With Viewport Prediction for VR Video Streaming in 5G H-CRAN," in IEEE Access, vol. 7, pp. 134187-134197, 2019 is available at https://dx.doi.org/10.1109/ACCESS.2019.2941646en_US
dc.subjectVR videoen_US
dc.subjectQuality of experience (QoE)en_US
dc.subjectResource allocationen_US
dc.subjectCellular networken_US
dc.subjectMulticasten_US
dc.subjectUnicasten_US
dc.subjectH-CRANen_US
dc.titleCMU-VP : cooperative multicast and unicast with viewport prediction for VR video streaming in 5G H-CRANen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage134187en_US
dc.identifier.epage134197en_US
dc.identifier.volume7en_US
dc.identifier.doi10.1109/ACCESS.2019.2941646en_US
dcterms.abstractVirtual reality (VR) is commonly regarded as one of 5G killer-applications. Transmission efficiency and quality of experience (QoE) are the most concerning issues for VR video streaming in 5G networks. Several multicast approaches were proposed to address these issues regardless of variance of personal viewports. In this paper, we explore a novel scheme combining multicast and unicast sessions in heterogeneous cloud-radio access networks (H-CRAN), in which a basic version of the video is transmitted to all users through the g-NB in a multicast session, and tiles of enhanced-version are transmitted to each viewer in a unicast session through its stationed remote radio head (RHH). To ensure the real-time content delivery, a user's viewport is predicted using a method based on historical trajectories and similarity of motion behavior, and then the tiles of predicted viewport in a version dependent on the channel quality are sent to the user in the unicast session. The scheme is formulated into a mixed-integer nonlinear problem (MINLP), and two near-optimal solutions are proposed to solve it by applying greedy approach and approximate approach, respectively. The simulation results show that our proposed scheme ensures better QoE under constrained bandwidth, and the proposed near-optimal solutions can efficiently solve the problem with low complexity and comparable performance.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationIEEE access, 17 Sept. 2019, v. 7, p. 134187-134197en_US
dcterms.isPartOfIEEE accessen_US
dcterms.issued2019-
dc.identifier.isiWOS:000498660800005-
dc.identifier.scopus2-s2.0-85077965907-
dc.description.validate202002 bcrc-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOSen_US
dc.description.pubStatusPublisheden_US
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