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Sensors 2019, 19(8), 1830; https://doi.org/10.3390/s19081830

Energy Efficient Resource Allocation for M2M Devices in 5G

1
Department of Computer Science and Engineering, University of Engineering and Technology, Lahore 54890, Pakistan
2
Sultan Quboos IT Chair, University of Engineering and Technology, Lahore 54890, Pakistan
3
Department of Computer Science and Engineering, University of Engineering and Technology, Lahore 54890, Pakistan
*
Author to whom correspondence should be addressed.
Received: 10 February 2019 / Revised: 20 March 2019 / Accepted: 25 March 2019 / Published: 17 April 2019
(This article belongs to the Section Internet of Things)
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Abstract

Resource allocation for machine-type communication (MTC) devices is one of the keys challenges in the 5G network as it affects the lifetime of battery powered devices and also the quality of service of the applications. MTC devices are battery restrained and cannot afford a lot of power consumption due to spectrum usage. In this paper, we propose a novel resource allocation algorithm termed threshold controlled access (TCA) protocol. We propose a novel technique of uplink resource allocation in which the devices make a decision of resource allocation blocks based on their battery status and related application’s power profile that eventually leads to required quality of service (QoS) metric. The first phase of the TCA algorithm selects the number of carriers to be allocated to a certain device for the better lifetime of low power MTC devices. In the second phase, the efficient solution is implemented through inducing a threshold value. A certain value of the threshold is selected through a mapping based on a QoS metric. The threshold enhances the selection of subcarriers for less powered devices, such as small e-health sensors. The algorithm is simulated for the physical layer of the 5G network. Simulation results show that the proposed algorithm is less complex and achieves better performance when compared to existing solutions in the literature. View Full-Text
Keywords: machine-to-machine; energy efficiency; resource allocation; 5G machine-to-machine; energy efficiency; resource allocation; 5G
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Ali, A.; Shah, G.A.; Arshad, J. Energy Efficient Resource Allocation for M2M Devices in 5G. Sensors 2019, 19, 1830.

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