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Fast Spectral Assessment for Handover Decisions in 5G Networks

机译:5G网络中切换决策的快速频谱评估

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In this paper, we present a UE-driven light-weight mechanism for fast handover decision and efficient WLAN selection in the context of 5G networks. As the network deployments are expected to be denser and the mobile user will be offered a multitude of alternative short coverage range options to have her mobile traffic served, her roaming decision will be performance critical. While the current 3GPP standardization considers the use of network performance statistics of nearby WLANs for the UE-driven roaming selection to address the uncertainty of the shared wireless medium, their collection and processing inevitably affects the mobile user performance and inserts an accuracy-performance tradeoff. We introduce a spectrum assessment framework, that is based on commercial hardware and open-source software, to evaluate the conditions on the nearby WLANs and let the UE to infer their performance with minimum overhead relying on Duty Cycle evaluation and the RSSI metrics. Our ready-to-be deployed solution leverages the use of off-the-shelf equipment and commercial devices and enables fast decision procedures for the WLAN selection with low collection and processing overhead. We evaluate our mechanism by conducting testbed experiments. The results reveal performance gains in terms of UE's achieved throughput when enabling the proposed framework to infer the spectral WLAN conditions and decide for the AP to roam.
机译:在本文中,我们提出了一种由UE驱动的轻量级机制,用于在5G网络的情况下进行快速切换决策和有效的WLAN选择。由于预计网络部署会更密集,并且将为移动用户提供多种替代的短覆盖范围选项来满足她的移动业务需求,因此她的漫游决定将对性能至关重要。尽管当前的3GPP标准化考虑将附近WLAN的网络性能统计信息用于UE驱动的漫游选择,以解决共享无线介质的不确定性,但它们的收集和处理不可避免地会影响移动用户的性能,并在准确性与性能之间进行权衡。我们引入基于商业硬件和开源软件的频谱评估框架,以评估附近WLAN的状况,并让UE依靠占空比评估和RSSI指标以最小的开销推断其性能。我们的即用型解决方案利用了现成的设备和商用设备,并为WLAN选择提供了快速的决策程序,而收集和处理开销却很低。我们通过进行试验台实验来评估我们的机制。结果表明,当使所提出的框架能够推断频谱WLAN条件并决定AP漫游时,就可以通过UE达到的吞吐量来提高性能。

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