LoRa Technology Demystified: From Link Behavior to Cell-Level Performance

Croce, Daniele; Gucciardo, Michele; Mangione, Stefano; Santaromita, Giuseppe; Tinnirello, Ilenia

doi:10.1109/twc.2019.2948872

Cited by 54 publications

(45 citation statements)

References 16 publications

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“…These sensors communicate with the GW module by means of different SFs, and as a communication channel, 868.3 MHz is used. For the conducted tests, the payload has been set to 12 bytes, due to considering this the average dimension of a LoRa packet [35]. In these experiments, a handful of test scenarios has been performed for the validation of the developed traffic generator.…”

Section: Lora Traffic Generator Development and Validationmentioning

confidence: 99%

LoRa Traffic Generator Based on Software Defined Radio Technology for LoRa Modulation Orthogonality Analysis: Empirical and Experimental Evaluation

Lavric¹,

Petrariu²,

Coca³

et al. 2020

Sensors

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The digital revolution has changed the way we implement and use connected devices and systems by offering Internet communication capabilities to simple objects around us. The growth of information technologies, together with the concept of the Internet of Things (IoT), exponentially amplified the connectivity capabilities of devices. Up to this moment, the Long Range (LoRa) communication technology has been regarded as the perfect candidate, created to solve the issues of the IoT concept, such as scalability and the possibility of integrating a large number of sensors. The goal of this paper is to present an analysis of the communication collisions that occur through the evaluation of performance level in various scenarios for the LoRa technology. The first part addresses an empirical evaluation and the second part presents the development and validation of a LoRa traffic generator. The findings suggest that even if the packet payload increases, the communication resistance to interferences is not drastically affected, as one may expect. These results are analyzed by using a novel Software Defined Radio (SDR) technology LoRa traffic generator, that ensures a high-performance level in terms of generating a large LoRa traffic volume. Despite the use of orthogonal variable spreading factor technique, within the same communication channel, the collisions between LoRa packets may dramatically decrease the communication performance level.

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Section: Lora Traffic Generator Development and Validationmentioning

confidence: 99%

LoRa Traffic Generator Based on Software Defined Radio Technology for LoRa Modulation Orthogonality Analysis: Empirical and Experimental Evaluation

Lavric¹,

Petrariu²,

Coca³

et al. 2020

Sensors

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“…The state of the art (Section IV) has modeled LoRa networks by using stochastic geometry [9,16,[18][19][20] or by extending well-known models for contention-based channel access [14,21,22]. However, these models consider simple network layouts with only one gateway [9,16,18,19], or make strict assumptions about the spatial distribution of nodes [20].…”

Section: Introductionmentioning

confidence: 99%

Modeling Communication Reliability in LoRa Networks with Device-level Accuracy

Toro-Betancur

Premsankar

Słabicki

et al. 2021

IEEE INFOCOM 2021 - IEEE Conference on Computer Communications

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Long Range (LoRa) is a low-power wireless communication technology for long-range connectivity, extensively used in the Internet of Things. Several works in the literature have analytically characterized the performance of LoRa networks, with particular focus on scalability and reliability. However, most of the related models are limited, as they cannot account for factors that occur in practice, or make strong assumptions on how devices are deployed in the network. This article proposes an analytical model that describes the delivery ratio in a LoRa network with device-level granularity. Specifically, it considers the impact of several key factors that affect real deployments, including multiple gateways and channel variation. Therefore, the proposed model can effectively evaluate the delivery ratio in realistic network topologies, without any restrictions on device deployment or configuration. It also accurately characterizes the delivery ratio of each device in a network, as demonstrated by extensive simulations in a wide variety of conditions, including diverse networks in terms of node deployment and link-level parameter settings. The proposed model provides a level of detail that is not available in the state of the art, and it matches the simulation results within an error of a few percentage points.

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“…frames that are set with different spreading factors (SF) are orthogonal to each other and do not cause interference, has been assumed considering that there is at least 16dB co-channel rejection between any different SF couples [4], [5], [6], [7]. This assumption however, has not been taken by others when analyzing the performance of LoRa networks [8], [9], [10], [11]. In order to have a more realistic scenario and include the effect of all possible interference, this letter also considers imperfect orthogonality between SFs.…”

Section: Introductionmentioning

confidence: 99%

“…Frame error and symbol rates were approximated through deriving low complexity formulas [5]. For a singlecell LoRa network under imperfect orthogonality condition, the success and coverage probabilities have been analytically analyzed [8], throughout of uplink has been theoretically analyzed [9], LoRa's link level performance and network capacity have been experimentally and analytically analyzed taking the frame transmission period into account [10] and experimental and simulations results have shown that packet loss due to imperfect orthogonality is an issue in LoRa network [11].…”

Section: Introductionmentioning

confidence: 99%

Analysis of the Reliability of LoRa

qadir

2021

IEEE Commun. Lett.

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This letter studies the performance of a single gateway LoRa system in the presence of different interference considering the imperfect orthogonality effect. It utilizes concepts of stochastic geometry to present a low-complexity approximate closed-form model for computing the success and coverage probabilities under these challenging conditions. Monte Carlo simulation results have shown that LoRa is not as theoretically described as a technology that can cover few to ten kilometers. It was found that in the presence of the combination of signal-tonoise ratio (SNR) and imperfect orthogonality between spreading factors (SF), the performance degrades dramatically beyond a couple of kilometers. However, better performance is observed when perfect orthogonality is considered and SNR is not included. Furthermore, the performance is annulus dependent and slightly improves at the border of the deployment cell annuli. Finally, the coverage probability declines exponentially as the average number of end devices grows.

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LoRa Technology Demystified: From Link Behavior to Cell-Level Performance

Cited by 54 publications

References 16 publications

LoRa Traffic Generator Based on Software Defined Radio Technology for LoRa Modulation Orthogonality Analysis: Empirical and Experimental Evaluation

LoRa Traffic Generator Based on Software Defined Radio Technology for LoRa Modulation Orthogonality Analysis: Empirical and Experimental Evaluation

Modeling Communication Reliability in LoRa Networks with Device-level Accuracy

Analysis of the Reliability of LoRa

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