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dc.contributor.authorChang, Chia-Weien_US
dc.contributor.authorLin, Yi-Haoen_US
dc.contributor.authorRen, Yien_US
dc.contributor.authorChen, Jyh-Chengen_US
dc.date.accessioned2018-08-21T05:56:44Z-
dc.date.available2018-08-21T05:56:44Z-
dc.date.issued2016-01-01en_US
dc.identifier.issn2334-0983en_US
dc.identifier.urihttp://hdl.handle.net/11536/146573-
dc.description.abstractCollecting data from a tremendous amount of Internet-of-Things (IoT) devices for next generation networks is a big challenge. A large number of devices may lead to severe congestion in Radio Access Network (RAN) and Core Network (CN). 3GPP has specified several mechanisms to handle the congestion caused by massive amounts of devices. However, detailed settings and strategies of them are not defined in the standards and are left for operators. In this paper, we propose two congestion control algorithms which efficiently reduce the congestion. Simulation results demonstrate that the proposed algorithms can achieve 20 similar to 40% improvement regarding accept ratio, overload degree and waiting time compared with those in LTE-A.en_US
dc.language.isoen_USen_US
dc.subjectcongestion controlen_US
dc.subjectM2Men_US
dc.subjectIoTen_US
dc.subjectLTE-Aen_US
dc.titleCongestion Control for Machine-Type Communications in LTE-A Networksen_US
dc.typeProceedings Paperen_US
dc.identifier.journal2016 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM)en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000401963301036en_US
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