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Energy Efficient Resource Allocation for M2M Devices in 5G

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...

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Detalles Bibliográficos
Autores principales: Ali, Anum, Shah, Ghalib A., Arshad, Junaid
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6514869/
https://www.ncbi.nlm.nih.gov/pubmed/30999622
http://dx.doi.org/10.3390/s19081830
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author Ali, Anum
Shah, Ghalib A.
Arshad, Junaid
author_facet Ali, Anum
Shah, Ghalib A.
Arshad, Junaid
author_sort Ali, Anum
collection PubMed
description 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.
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spelling pubmed-65148692019-05-30 Energy Efficient Resource Allocation for M2M Devices in 5G Ali, Anum Shah, Ghalib A. Arshad, Junaid Sensors (Basel) Article 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. MDPI 2019-04-17 /pmc/articles/PMC6514869/ /pubmed/30999622 http://dx.doi.org/10.3390/s19081830 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Ali, Anum
Shah, Ghalib A.
Arshad, Junaid
Energy Efficient Resource Allocation for M2M Devices in 5G
title Energy Efficient Resource Allocation for M2M Devices in 5G
title_full Energy Efficient Resource Allocation for M2M Devices in 5G
title_fullStr Energy Efficient Resource Allocation for M2M Devices in 5G
title_full_unstemmed Energy Efficient Resource Allocation for M2M Devices in 5G
title_short Energy Efficient Resource Allocation for M2M Devices in 5G
title_sort energy efficient resource allocation for m2m devices in 5g
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6514869/
https://www.ncbi.nlm.nih.gov/pubmed/30999622
http://dx.doi.org/10.3390/s19081830
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