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

Article


Afrin, Nusrat, Brown, Jason and Khan, Jamil Y.. 2022. "A Multi-Service Adaptive Semi-Persistent LTE Uplink Scheduler for Low Power M2M Devices." Future Internet. 14 (4), pp. 1-28. https://doi.org/10.3390/fi14040107
Article Title

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

ERA Journal ID212586
Article CategoryArticle
AuthorsAfrin, Nusrat (Author), Brown, Jason (Author) and Khan, Jamil Y. (Author)
Journal TitleFuture Internet
Journal Citation14 (4), pp. 1-28
Article Number107
Number of Pages28
Year2022
PublisherMDPI AG
Place of PublicationSwitzerland
ISSN1999-5903
Digital Object Identifier (DOI)https://doi.org/10.3390/fi14040107
Web Address (URL)https://www.mdpi.com/1999-5903/14/4/107
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.

KeywordsLTE; Machine-to-Machine; Internet of Things; packet scheduling; channel utilization; DRX; low-power M2M; QoS
ANZSRC Field of Research 2020400604. Network engineering
400608. Wireless communication systems and technologies (incl. microwave and millimetrewave)
Byline AffiliationsUniversity of Newcastle
School of Mechanical and Electrical Engineering
Institution of OriginUniversity of Southern Queensland
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