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ToolsAl-Gumaei, Yousef A., Aslam, Nauman, Chen, Xiaomin, Raza, Mohsin and Ansari, Rafay Iqbal (2022) Optimizing power allocation in LoRaWAN IoT applications. IEEE Internet of Things Journal, 9 (5). pp. 3429-3442. ISSN 2327-4662
Full text not available from this repository. (Request a copy)Abstract
Long-range wide-area network (LoRaWAN) is one of the most promising IoT technologies that are widely adopted in low-power wide-area networks (LPWANs). LoRaWAN faces scalability issues due to a large number of nodes connected to the same gateway and sharing the same channel. Therefore, LoRa networks seek to achieve two main objectives: 1) successful delivery rate and 2) efficient energy consumption. This article proposes a novel game-theoretic framework for LoRaWAN named best equal LoRa (BE-LoRa), to jointly optimize the packet delivery ratio and the energy efficiency (bit/Joule). The utility function of the LoRa node is defined as the ratio of the throughput to the transmit power. LoRa nodes act as rational users (players) which seek to maximize their utility. The aim of the BE-LoRa algorithm is to maximize the utility of LoRa nodes while maintaining the same signal-to-interference-and-noise-ratio (SINR) for each spreading factor (SF). The power allocation algorithm is implemented at the network server, which leads to an optimum SINR, SFs, and transmission power settings of all nodes. Numerical and simulation results show that the proposed BE-LoRa power allocation algorithm has a significant improvement in the packet delivery ratio and energy efficiency as compared to the adaptive data rate (ADR) algorithm of legacy LoRaWAN. For instance, in very dense networks (624 nodes), BE-LoRa can improve the delivery ratio by 17.44% and reduce power consumed by 46% compared to LoRaWAN ADR.
| Item Type: | Article |
|---|---|
| Additional Information: | Publisher Copyright: © 2014 IEEE. |
| Uncontrolled Keywords: | game theory,internet of things,long-range wide-area network (lorawan),power allocation,signal-to-interference-and-noise-ratio (sinr) balancing,signal processing,information systems,hardware and architecture,computer science applications,computer networks and communications,sdg 7 - affordable and clean energy ,/dk/atira/pure/subjectarea/asjc/1700/1711 |
| Faculty \ School: | Faculty of Science > School of Computing Sciences |
| UEA Research Groups: | Faculty of Science > Research Groups > Cyber Intelligence and Networks |
| Related URLs: | |
| Depositing User: | LivePure Connector |
| Date Deposited: | 18 Jun 2025 13:30 |
| Last Modified: | 23 Jun 2025 00:29 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/99628 |
| DOI: | 10.1109/JIOT.2021.3098477 |
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