Minimum Throughput Maximization in LoRa Networks Powered by Ambient Energy Harvesting

Benkhelifa, Fatma; Qin, Zhijin; McCann, Julie A.

doi:10.1109/icc.2019.8761478

Cited by 24 publications

(17 citation statements)

References 16 publications

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“…From the simulation results, it is shown that the proposed mechanism improves the fairness, data rates, and throughput performance when compared to the baseline algorithms. In [116], a resource allocation algorithm for LoRaWAN is introduced, which involves energy harvesting. The authors also provide a model to optimize SF allocation, energy harvesting duration and power devices for IoT transmission.…”

Section: B Sensor/iot Device Side 1) Resource Allocationmentioning

confidence: 99%

Multi-Layered Energy Efficiency in LoRa-WAN Networks: A Tutorial

et al. 2022

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Emerging Internet-of-Things (IoT) applications are driving increasing demand for advanced services in wireless networks, prompting the development of new technologies to address the associated challenges. Energy efficiency of IoT standards is a key feature targeted by research efforts and industrial activities, leading to an extensive and growing number of innovative solutions. Low Power Wide Area Networks (LPWANs) define a class of wireless communication technologies seen as highly relevant for future IoT development given its long communication range, low-cost devices and interesting energy management. Long Range Wide Area Network (LoRaWAN) is acknowledged to be the dominant IoT communication technology. It has allowed broad deployment and unlocked new IoT applications such as smart cities, asset tracking, etc. This article provides a comprehensive tutorial on the LoRa standard, and surveys existing solutions, hot topics and future insights for building energy efficient IoT infrastructures and IoT devices. Indeed, energy efficiency is one of the key factors for successful and sustainable deployments of IoT applications. More precisely, this article discusses how to meet LoRa/LoRaWAN energy efficiency across physical layer, medium access control layer, and network layer. Next, extensive pioneering solutions from related literature are compared and assessed. Finally, insightful conclusions are drawn, and open problems are listed at the end of this article.

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Section: B Sensor/iot Device Side 1) Resource Allocationmentioning

confidence: 99%

Multi-Layered Energy Efficiency in LoRa-WAN Networks: A Tutorial

et al. 2022

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“…Benkhelifa et al [94] designed a resource allocation algorithm for LoRaWAN, which involved energy harvesting. The authors also developed a model to optimize the SF assignment, energy harvesting time duration, and power devices for IoT transmission.…”

Section: Multiple Parametermentioning

confidence: 99%

A Survey on Long-Range Wide-Area Network Technology Optimizations

et al. 2021

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Long-Range Wide-Area Network (LoRaWAN) enables flexible long-range service communications with low power consumption which is suitable for many IoT applications. The densification of LoRaWAN, which is needed to meet a wide range of IoT networking requirements, poses further challenges. For instance, the deployment of gateways and IoT devices are widely deployed in urban areas, which leads to interference caused by concurrent transmissions on the same channel. In this context, it is crucial to understand aspects such as the coexistence of IoT devices and applications, resource allocation, Media Access Control (MAC) layer, network planning, and mobility support, that directly affect LoRaWAN's performance. We present a systematic review of state-of-the-art works for LoRaWAN optimization solutions for IoT networking operations. We focus on five aspects that directly affect the performance of LoRaWAN. These specific aspects are directly associated with the challenges of densification of LoRaWAN. Based on the literature analysis, we present a taxonomy covering five aspects related to LoRaWAN optimizations for efficient IoT networks. Finally, we identify key research challenges and open issues in LoRaWAN optimizations for IoT networking operations that must be further studied in the future.

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“…Benkhelifa el al. studied in Reference [ 1 ] the resource allocation in LoRa networks supplied by ambient energy harvesting. Mabon et al presented in Reference [ 25 ] a prototype of an energy harvesting LoRa platform with an accurate sizing of both the solar cell and the battery.…”

Section: Related Workmentioning

confidence: 99%

“…Such technology offers a link range of several kilometers and a low power consumption, but at the cost of small data rate. Many technologies belong to LPWAN category, such as SigFox, Narrowband IoT, Weightless, and LoRa [ 1 ]. Among these existing LPWANs sets, LoRa is the most popular due to its open communication protocol (LoRaWAN) and its ability to achieve a long range and to recover data from weak signals even below the noise floor [ 2 ].…”

Section: Introductionmentioning

confidence: 99%

How Can Wake-up Radio Reduce LoRa Downlink Latency for Energy Harvesting Sensor Nodes?

Djidi

Gautier

Courtay

et al. 2021

Sensors

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LoRa is popular for internet of things applications as this communication technology offers both a long range and a low power consumption. However, LoRaWAN, the standard MAC protocol that uses LoRa as physical layer, has the bottleneck of a high downlink latency to achieve energy efficiency. To overcome this drawback we explore the use of wake-up radio combined with LoRa, and propose an adequate MAC protocol that takes profit of both these heterogeneous and complementary technologies. This protocol allows an opportunistic selection of a cluster head that forwards commands from the gateway to the nodes in the same cluster. Furthermore, to achieve self-sustainability, sensor nodes might include an energy harvesting sub-system, for instance to scavenge energy from the light, and their quality of service can be tuned, according to their available energy. To have an effective self-sustaining LoRa system, we propose a new energy manager that allows less fluctuations of the quality of service between days and nights. Latency and energy are modeled in a hybrid manner, i.e., leveraging microbenchmarks on real hardware platforms, to explore the influence of the energy harvesting conditions on the quality of service of this heterogeneous network. It is clearly demonstrated that the cooperation of nodes within a cluster drastically reduces the latency of LoRa base station commands, e.g., by almost 90% compared to traditional LoRa scheme for a 10 nodes cluster.

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Minimum Throughput Maximization in LoRa Networks Powered by Ambient Energy Harvesting

Cited by 24 publications

References 16 publications

Multi-Layered Energy Efficiency in LoRa-WAN Networks: A Tutorial

Multi-Layered Energy Efficiency in LoRa-WAN Networks: A Tutorial

A Survey on Long-Range Wide-Area Network Technology Optimizations

How Can Wake-up Radio Reduce LoRa Downlink Latency for Energy Harvesting Sensor Nodes?

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