A study of Bayesian scheduling for M2M traffic in wireless LTE network

Citation

Khoo, Siew Kay and Wee, Kuok Kwee and Ooi, Shih Yin (2017) A study of Bayesian scheduling for M2M traffic in wireless LTE network. In: 2017 International Conference on Robotics, Automation and Sciences (ICORAS), 27-29 Nov. 2017, Melaka.

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Abstract

In the event of phenomenal growth in Internet of Things (IoT), Machine-to-Machine (M2M) devices are projected to reach figure of multiple billions in foreseeable future. Operators around the world are aggressively refarming their spectrum from older network and moving quickly to Long Term Evolution (LTE) for guarantee of future-proof services. With every new M2M application being invented or deployed at this pace, unprecedented factors are unceasingly induced to existing LTE protocols which caused undesirable performance degradation. In this paper, a realistic LTE network environment are modelled and simulated with tractable M2M traffic modules to observe such impacts on conventional scheduling schemes and to identify the major causes. A prominent conventional Bayesian approach is hence adopted for revision to adapt the new M2M traffics. The results obtained shown that the proposed M2M-enabled True Bayesian Estimate (TBE-M) algorithm is capable of outperforming the conventional TBE on a great scale

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Machine-to machine communications
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5101-6720 Telecommunication. Including telegraphy, telephone, radio, radar, television
Divisions: Faculty of Information Science and Technology (FIST)
Depositing User: Ms Rosnani Abd Wahab
Date Deposited: 20 Apr 2021 19:35
Last Modified: 20 Apr 2021 19:35
URII: http://shdl.mmu.edu.my/id/eprint/7634

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