Comparative Performance Analysis of Empirical Propagation Models for LoRaWAN 868MHz in an Urban Scenario

Harinda, Eugen; Hosseinzadeh, Salaheddin; Larijani, Hadi; Gibson, Ryan M.

doi:10.1109/wf-iot.2019.8767245

Cited by 41 publications

(34 citation statements)

References 23 publications

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“…Currently, there are some empirical propagation models used to estimate packet loss versus distance in urban and sub-urban areas [ 14 , 15 , 43 ]. However, although the existing models were derived from experimental data using different configurations and propagation environments, there is no model which considers transmission over water surfaces where antennas are placed at low heights in relation to the water surface.…”

Section: Analysis Of Wireless Propagation Model For Lora Technologmentioning

confidence: 99%

“…Existing propagation models ([ 14 , 15 ] and others) take into account node and gateway heights. However, a vast majority of the works reported in the literature (e.g., References [ 16 , 17 ]), in which several scenarios have been considered to evaluate LoRa, mainly consider nodes placed at high heights in order to achieve large communication ranges.…”

Section: Introductionmentioning

confidence: 99%

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Evaluation of LoRa Technology in Flooding Prevention Scenarios

Cecílio

Ferreira

Casimiro

2020

Sensors

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Global climate change originates frequent floods that may cause severe damage, justifying the need for real-time remote monitoring and alerting systems. Several works deal with LoRa (Long Range) communications over land and in the presence of obstacles, but little is known about LoRa communication reliability over water, as it may happen in real flooding scenarios. One aspect that is known to influence the communication quality is the height at which nodes are placed. However, its impact in water environments is unknown. This is an important aspect that may influence the location of sensor nodes and the network topology. To fill this gap, we conducted several experiments using a real LoRa deployment to evaluate several features related to data communication. We considered two deployment scenarios corresponding to countryside and estuary environments. The nodes were placed at low heights, communicating, respectively, over the ground and over the water. Measurements for packet loss, received signal strength indicator (RSSI), signal-to-noise ratio (SNR) and round-trip time (RTT) were collected during a period of several weeks. Results for both scenarios are presented and compared in this paper. One important conclusion is that the communication distance and reliability are significantly affected by tides when the communication is done over the water and nodes are placed at low heights. Based on the RTT measurements and on the characteristics of the hardware, we also derive a battery lifetime estimation model that may be helpful for the definition of an adequate maintenance plan.

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Section: Analysis Of Wireless Propagation Model For Lora Technologmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Evaluation of LoRa Technology in Flooding Prevention Scenarios

Cecílio

Ferreira

Casimiro

2020

Sensors

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“…The comparison of results obtained by a radio planning tool and measurements from a real LoRaWAN deployment is shown in References [18,19,20]. The authors of Reference [18] estimate the coverage range using the Okumura-Hata model for three different scenarios—urban, suburban and rural.…”

Section: Related Workmentioning

confidence: 99%

“…Their estimation from the radio planning tool is closer to the coverage range seen in the experimental measurements. The authors of Reference [19] compare real-life LoRaWAN data collected in the city of Glasgow to a LoRaWAN data generated using the ns-3 open-source simulator for three propagation models—Okumura-Hata, COST-231 Hata and COST-231 Walfish-Ikegami. The Okumura-Hata propagation model has the best fit to the measured data.…”

Section: Related Workmentioning

confidence: 99%

Temperature Impact in LoRaWAN—A Case Study in Northern Sweden

Bezerra

Åhlund

Saguna

et al. 2019

Sensors

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LoRaWAN has become popular as an IoT enabler. The low cost, ease of installation and the capacity of fine-tuning the parameters make this network a suitable candidate for the deployment of smart cities. In northern Sweden, in the smart region of Skellefteå, we have deployed a LoRaWAN to enable IoT applications to assist the lives of citizens. As Skellefteå has a subarctic climate, we investigate how the extreme changes in the weather happening during a year affect a real LoRaWAN deployment in terms of SNR, RSSI and the use of SF when ADR is enabled. Additionally, we evaluate two propagation models (Okumura-Hata and ITM) and verify if any of those models fit the measurements obtained from our real-life network. Our results regarding the weather impact show that cold weather improves the SNR while warm weather makes the sensors select lower SFs, to minimize the time-on-air. Regarding the tested propagation models, Okumura-Hata has the best fit to our data, while ITM tends to overestimate the RSSI values.

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“…The studies in [9]- [13] have used only measurements to understand the behavior of air channel propagation on LoRaWAN network operations, but this is an expensive approach as best practices involve taking measurements at the later stages of network optimization. To validate the applicability of empirical propagation models for LoRaWAN in the city environment, our previous work in [14] showed less satisfactory empirical models' prediction performance against measurements. Trace-driven simulation can bridge the gap between measurement and simulation to evaluate RF propagation models' performance for LoRaWAN networks.…”

Section: Introductionmentioning

confidence: 99%

Trace-Driven Simulation of LoRaWAN Air Channel Propagation in an Urban Scenario

Harinda¹,

Larijani²,

Gibson³

2020

Adv. sci. technol. eng. syst. j.

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Long-range, Low-Power Wide Area Network (LoRaWAN) is a very scalable solution for the Internet of Things (IoT). Due to the air channel environment's complexity, connectivity is a crucial parameter for successfully planning and deploying the IoT networks. Measurements and simulations have been used to evaluate LoRaWAN propagation models in the Urban environment, but it is a challenging task. While practical propagation evaluation has been prohibitively expensive, the theoretical modeling results have been less accurate. This paper uses real-world measurements and a trace-driven simulation technique to evaluate the RF propagation models' prediction performance for LoRaWAN 868 MHz propagation. First, a novel LoRaWAN tracedriven simulation of Glasgow city centre has been performed. Second, LoRaWAN 868 MHz measurements have been used to perform a critical analysis of LoRaWAN trace-driven Radio Frequency (RF) propagation models and validation. The processed trace dataset is composed of GPS coordinates, and the corresponding LoRaWAN received signal strength. The dataset has been extracted from 5017 datasets of LoRaWAN measurements taken from Glasgow city centre. A trace simulation program built-in ICS-Telecom was used to simulate LoRaWAN propagation in the real-world urban environment. Comparison of LoRaWAN simulation traces and the real-world data was performed to evaluate the prediction performance accuracy of Deygout 94, ITU-R 525/526, and COST-Walfish Ikegami (COST-WI) propagation models. All models overestimated LoRaWAN trace-simulated RSS levels in comparison to collected measurement samples. While Deygout 94 prediction accuracy was higher with mean absolute error (MAE) at 0.83 dBm and standard deviation (SD) at 4.17 dBm, COST-WI performed poorly with MAE and SD at 2.87 dBm and 10.96 dBm respectively.

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Comparative Performance Analysis of Empirical Propagation Models for LoRaWAN 868MHz in an Urban Scenario

Cited by 41 publications

References 23 publications

Evaluation of LoRa Technology in Flooding Prevention Scenarios

Evaluation of LoRa Technology in Flooding Prevention Scenarios

Temperature Impact in LoRaWAN—A Case Study in Northern Sweden

Trace-Driven Simulation of LoRaWAN Air Channel Propagation in an Urban Scenario

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