Kostas Chounos, Stratos Keranidis, A. Apostolaras, T. Korakis
{"title":"Fast Spectral Assessment for Handover Decisions in 5G Networks","authors":"Kostas Chounos, Stratos Keranidis, A. Apostolaras, T. Korakis","doi":"10.1109/CCNC.2019.8651673","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":285899,"journal":{"name":"2019 16th IEEE Annual Consumer Communications & Networking Conference (CCNC)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 16th IEEE Annual Consumer Communications & Networking Conference (CCNC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCNC.2019.8651673","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
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.