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Scheduling for Machine Type Communications in LTE Systems
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Publication Year
2018-11-16
Journal
9th International Conference on Information and Communication Technology Convergence: ICT Convergence Powered by Smart Intelligence, ICTC 2018
Publisher
Institute of Electrical and Electronics Engineers Inc.
Citation
9th International Conference on Information and Communication Technology Convergence: ICT Convergence Powered by Smart Intelligence, ICTC 2018, pp.889-891
Keyword
5G/LTEMTCScheduling
Mesh Keyword
5G/LTEAdvanced systemsCellular networkChannel feedbacksInternet of Things (IOT)Machine type communicationsMachinetype communication (MTC)Time-controlled
All Science Classification Codes (ASJC)
Computer Networks and CommunicationsComputer Science ApplicationsInformation SystemsInformation Systems and ManagementArtificial Intelligence
Abstract
To accommodate the massive connectivity of Internet-of-Things (IoT) such as a smart meter application for cellular networks, 3GPP has standardized Machine Type Communication (MTC) and cellular IoT. The data transmission of such IoT exhibits a time-controlled and an event-driven feature which delivers short messages with low data rate but supports massive connectivity. In MTC and its advanced system including eMTC and 5G-NR, legacy data and IoT data share radio resource; thus, any existing scheduler can handle both types of data separately. In this paper, we prove that existing schedulers that favor instantaneous channel quality do not work effectively for IoT data. Based on this property, we suggest a modified First Maximum Expansion (m-FME) algorithm that removes channel feedback. Through simulation, we confirm that m-FME outperforms existing schedulers.
Language
eng
URI
https://aurora.ajou.ac.kr/handle/2018.oak/36287
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85059473461&origin=inward
DOI
https://doi.org/10.1109/ictc.2018.8539375
Journal URL
http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=8509497
Type
Conference
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Choi, Youngjune최영준
Department of Software and Computer Engineering
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