A Multi-Service Adaptive Semi-Persistent LTE Uplink Scheduler for Low Power M2M Devices

Afrin, Nusrat and Brown, Jason ORCID: https://orcid.org/0000-0002-0698-5758 and Khan, Jamil Y. (2022) A Multi-Service Adaptive Semi-Persistent LTE Uplink Scheduler for Low Power M2M Devices. Future Internet, 14 (4):107. pp. 1-28.

[img]
Preview
Text (Published Version)
2022 MDPI Future Internet Published Paper.pdf
Available under License Creative Commons Attribution 4.0.

Download (2MB) | Preview

Abstract

The prominence of Machine-to-Machine (M2M) communications in the future wide area communication networks place various challenges to the cellular technologies such as the Long Term Evolution (LTE) standard, owing to the large number of M2M devices generating small bursts of infrequent data packets with a wide range of delay requirements. The channel structure and Quality of Service (QoS) framework of LTE networks fail to support M2M traffic with multiple burst sizes and QoS requirements while a bottleneck often arises from the limited control resources to communicate future uplink resource allocations to the M2M devices. Moreover, many of the M2M devices are battery-powered and require a low-power consuming wide area technology for wide-spread deployments. To alleviate these issues, in this article we propose an adaptive semipersistent scheduling (SPS) scheme for the LTE uplink which caters for multi-service M2M traffic classes with variable burst sizes and delay tolerances. Instead of adhering to the rigid LTE QoS framework, the proposed algorithm supports variation of uplink allocation sizes based on queued data length yet does not require control signaling to inform those allocations to the respective devices. Both the eNodeB and the M2M devices can determine the precise uplink resource allocation related parameters based on their mutual knowledge, thus omitting the burden of regular control signaling exchanges. Based on a control parameter, the algorithm can offer different capacities and levels of QoS satisfaction to different traffic classes. We also introduce a pre-emptive feature by which the algorithm can prioritize new traffic with low delay tolerance over ongoing delay-tolerant traffic. We also build a model for incorporating the Discontinuous Reception (DRX) mechanism in synchronization with the adaptive SPS transmissions so that the UE power consumption can be significantly lowered, thereby extending their battery lives. The simulation and performance analysis of the proposed scheme shows significant improvement over the traditional LTE scheduler in terms of QoS satisfaction, channel utilization and low power requirements of multi-service M2M traffic.


Statistics for USQ ePrint 47800
Statistics for this ePrint Item
Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Faculty/School / Institute/Centre: Current – Faculty of Health, Engineering and Sciences - School of Engineering (1 Jan 2022 -)
Faculty/School / Institute/Centre: Current – Faculty of Health, Engineering and Sciences - School of Engineering (1 Jan 2022 -)
Date Deposited: 21 Apr 2022 02:58
Last Modified: 21 Apr 2022 02:58
Uncontrolled Keywords: LTE; Machine-to-Machine; Internet of Things; packet scheduling; channel utilization; DRX; low-power M2M; QoS
Fields of Research (2020): 40 ENGINEERING > 4006 Communications engineering > 400604 Network engineering
40 ENGINEERING > 4006 Communications engineering > 400608 Wireless communication systems and technologies (incl. microwave and millimetrewave)
Socio-Economic Objectives (2020): 22 INFORMATION AND COMMUNICATION SERVICES > 2201 Communication technologies, systems and services > 220103 Mobile technologies and communications
22 INFORMATION AND COMMUNICATION SERVICES > 2201 Communication technologies, systems and services > 220102 Internet protocols (ip)
22 INFORMATION AND COMMUNICATION SERVICES > 2201 Communication technologies, systems and services > 220107 Wireless technologies, networks and services
Identification Number or DOI: https://doi.org/10.3390/fi14040107
URI: http://eprints.usq.edu.au/id/eprint/47800

Actions (login required)

View Item Archive Repository Staff Only