Abstract
The proliferation demand of mobile users (MUs) for video contents, which will occupy up to 78% of data traffic by 2021, poses a serious challenge of system delivery capacity to the macro base stations (MBSs) and the small cell base stations, e.g., femtocell base stations (FBSs), in 5G networks. In this paper, we propose a social-aware caching and resource sharing (SCS) scheme that can help the MBSs and the FBSs relax the backhaul links and provide the MUs with high system delivery capacity. Particularly, we formulate an SCS optimization problem under the constraints on the number of replicas of each video cached in the FBSs and the target signal to interference plus noise ratio (SINR) of the cellular users (CUs) that share the downlink resources. This problem is then solved for maximum system delivery capacity by finding the best placements to cache the videos in the FBSs and the best device-to-device (D2D) pairs shared the same downlink resources with the CUs to offload the videos over D2D communications. Importantly, the behavior of MUs to access the videos and the social relationship of each D2D pair are considered in the SCS optimization problem to efficiently improve the system performance. Simulation results are shown to demonstrate the benefits of the proposed SCS scheme compared to other conventional schemes.
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Acknowledgement
This work is supported in part by Newton Prize 2017 and by a Research Environment Links grant, ID 339568416, under the Newton Programme Vietnam partnership. The grant is funded by the UK Department of Business, Energy and Industrial Strategy (BEIS) and delivered by the British Council. For further information, please visit www.newtonfund.ac.uk.
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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Bui, MP., Vo, NS., Nguyen, TT., Tran, QN., Tran, AT. (2019). Social-Aware Caching and Resource Sharing Optimization for Video Delivering in 5G Networks. In: Duong, T., Vo, NS., Phan, V. (eds) Quality, Reliability, Security and Robustness in Heterogeneous Systems. Qshine 2018. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 272. Springer, Cham. https://doi.org/10.1007/978-3-030-14413-5_6
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