A Novel Collision-Aware Adaptive Data Rate Algorithm for LoRaWAN Networks

Marini, Riccardo; Cerroni, Walter; Buratti, Chiara

doi:10.1109/jiot.2020.3020189

Cited by 53 publications

(25 citation statements)

References 30 publications

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“…The ADR algorithm is specifically designed to increase the data rate and reduce the energy consumed by the ED. It is not specified in the standard; however, Semtech provides a recommendation in [23] and most of NSs, to the best of our knowledge, operate based on it; its performance has been evaluated in [24]. Note that ADR should be used only if an ED operates in sufficiently stable RF conditions (e.g., static devices with fixed locations).…”

mentioning

confidence: 99%

LoRaWANSim: A Flexible Simulator for LoRaWAN Networks

Marini

Mikhaylov²,

Pasolini³

et al. 2021

Sensors

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Among the low power wide area network communication protocols for large scale Internet of Things, LoRaWAN is considered one of the most promising, owing to its flexibility and energy-saving capabilities. For these reasons, during recent years, the scientific community has invested efforts into assessing the fundamental performance limits and understanding the trade-offs between the parameters and performance of LoRaWAN communication for different application scenarios. However, this task cannot be effectively accomplished utilizing only analytical methods, and precise network simulators are needed. To that end, this paper presents LoRaWANSim, a LoRaWAN simulator implemented in MATLAB, developed to characterize the behavior of LoRaWAN networks, accounting for physical, medium access control and network aspects. In particular, since many simulators described in the literature are deployed for specific research purposes, they are usually oversimplified and hold a number of assumptions affecting the accuracy of their results. In contrast, our simulator has been developed for the sake of completeness and it is oriented towards an accurate representation of the LoRaWAN at the different layers. After a detailed description of the simulator, we report a validation of the simulator itself and we then conclude by presenting some results of its use revealing notable and non-intuitive trade-offs present in LoRaWAN. Such simulator will be made available via open access to the research community.

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confidence: 99%

LoRaWANSim: A Flexible Simulator for LoRaWAN Networks

Marini

Mikhaylov²,

Pasolini³

et al. 2021

Sensors

Self Cite

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“…In [142], a new ADR algorithm called CA-ADR is proposed for the LoRaWAN network to assign data rates to EDs by taking the collision probability at the MAC layer into account. The new algorithm was compared to two benchmark solutions using simulation and experimental approaches under different performance metrics.…”

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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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“…R k is the probability that an ED of SF k is active (i.e. in transmission mode); T in,k is the average packet inter arrival time and it is assumed to be the same for all SFs, i.e., T in,k = T in , ∀k; R k is the bit rate of SF k and is given by R k = k Bw 2 k 4 4+Cr [2]; and L pac,k is the packet length (in bits) of SF k and is given by [21] L pac,k = k ((N pre + 4.25)+8+…”

Section: A Coverage Probabilitymentioning

confidence: 99%