LoRa Performance in Industrial Environments: Analysis of Different ADR Algorithms

Vergel, Angelo Joseph Soto; Arismendy, Luis; Bornacelli-Duran, Robinson; Cárdenas, Carlos Alberto Murillo; Montero-Arevalo, Brayan; Rivera, Emanuel; Calle, María; Candelo-Becerra, John E.

doi:10.1109/tii.2023.3240696

Cited by 9 publications

(6 citation statements)

References 28 publications

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“…Focusing on LoRaWAN, it is worth mentioning FLoRa [23], based on the OMNeT++ engine and the INET framework; LoRaSim [24], a discrete event simulator exploiting the aforementioned SimPy Python engine; and the LoRaWAN modules implemented in ns3 [25]. A more exhaustive overview of simulation and emulation platforms targeting LoRaWAN is described in [26].…”

Section: Related Workmentioning

confidence: 99%

End-to-End Emulation of LoRaWAN Architecture and Infrastructure in Complex Smart City Scenarios Exploiting Containers

Gaffurini,

Flammini,

Ferrari

et al. 2024

Sensors

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In a LoRaWAN network, the backend is generally distributed as Software as a Service (SaaS) based on container technology, and recently, a containerized version of the LoRaWAN node stack is also available. Exploiting the disaggregation of LoRaWAN components, this paper focuses on the emulation of complex end-to-end architecture and infrastructures for smart city scenarios, leveraging on lightweight virtualization technology. The fundamental metrics to gain insights and evaluate the scaling complexity of the emulated scenario are defined. Then, the methodology is applied to use cases taken from a real LoRaWAN application in a smart city with hundreds of nodes. As a result, the proposed approach based on containers allows for the following: (i) deployments of functionalities on diverse distributed hosts; (ii) the use of the very same SW running on real nodes; (iii) the simple configuration and management of the emulation process; (iv) affordable costs. Both premise and cloud servers are considered as emulation platforms to evaluate the resource request and emulation cost of the proposed approach. For instance, emulating one hour of an entire LoRaWAN network with hundreds of nodes requires very affordable hardware that, if realized with a cloud-based computing platform, may cost less than USD 1.

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Section: Related Workmentioning

confidence: 99%

End-to-End Emulation of LoRaWAN Architecture and Infrastructure in Complex Smart City Scenarios Exploiting Containers

Gaffurini,

Flammini,

Ferrari

et al. 2024

Sensors

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show abstract

“…Using F-QoS, the authors also suggest a sampling approach where radio transmissions should be at least three times the desired final sampling rate to ensure data reliability. Moreover, the authors in [35] evaluate LoRaWAN performance with six different ADR algorithms in an industrial context using the FLoRa framework and an Omnet++ testbed. Analyses focus on packet delivery and energy consumption according to gateway position and data traffic.…”

Section: Related Workmentioning

confidence: 99%

Performance Evaluation of LoRa Communications in Harsh Industrial Environments

Aarif,

Tabaa,

Hachimi

2023

JSAN

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LoRa technology is being integrated into industrial applications as part of Industry 4.0 owing to its longer range and low power consumption. However, noise, interference, and the fading effect all have a negative impact on LoRa performance in an industrial environment, necessitating solutions to ensure reliable communication. This paper evaluates and compares LoRa’s performance in terms of packet error rate (PER) with and without forward error correction (FEC) in an industrial environment. The impact of integrating an infinite impulse response (IIR) or finite impulse response (FIR) filter into the LoRa architecture is also evaluated. Simulations are carried out in MATLAB at 868 MHz with a bandwidth of 125 kHz and two spreading factors of 7 and 12. Many-to-one and one-to-many communication modes are considered, as are line of sight (LOS) and non-line of Sight (NLOS) conditions. Simulation results show that, compared to an environment with additive white Gaussian noise (AWGN), LoRa technology suffers a significant degradation of its PER performance in industrial environments. Nevertheless, the use of forward error correction (FEC) contributes positively to offsetting this decline. Depending on the configuration and architecture examined, the gain in signal-to-noise ratio (SNR) using a 4/8 coding ratio ranges from 7 dB to 11 dB. Integrating IIR or FIR filters also boosts performance, with additional SNR gains ranging from 2 dB to 6 dB, depending on the simulation parameters.

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“…Various schemes for reducing the packet collision and improving the packet delivery rate have been considered. The performance of LoRa under the industrial application with various algorithms of the adaptive data rate (ADR) is clarified in [ 13 ]. When the parameters of the LoRa format, such as packet length and spreading factor, are changed, the packet error rate is evaluated [ 14 ].…”

Section: Introductionmentioning

confidence: 99%

An Environment-Aware Adaptive Data-Gathering Method for Packet-Level Index Modulation in LPWA

Takyu,

Takeda,

Miyamoto

et al. 2024

Sensors

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Low-power wide-area (LPWA) is a communication technology for the IoT that allows low power consumption and long-range communication. Additionally, packet-level index modulation (PLIM) can transmit additional information using multiple frequency channels and time slots. However, in a competitive radio access environment, where multiple sensors autonomously determine packet transmission, packet collisions occur when transmitting the same information. The packet collisions cause a reduction in the throughput. A method has been proposed to design a mapping table that shows the correspondence between indexes and information using a packet collision minimization criterion. However, the effectiveness of this method depends on how the probability of the occurrence of the information to be transmitted is modeled. We propose an environment-aware adaptive data-gathering method that identifies the location of factors affecting sensor information and constructs a model for the probability of the occurrence of sensor information. The packet collision rate of the environment-aware adaptive data-gathering method was clarified through computer simulations and actual experiments on a 429 MHz LPWA. We confirm that the proposed scheme improves the packet collision rate by 15% in the computer simulation and 30% in the experimental evaluation, respectively.

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LoRa Performance in Industrial Environments: Analysis of Different ADR Algorithms

Cited by 9 publications

References 28 publications

End-to-End Emulation of LoRaWAN Architecture and Infrastructure in Complex Smart City Scenarios Exploiting Containers

End-to-End Emulation of LoRaWAN Architecture and Infrastructure in Complex Smart City Scenarios Exploiting Containers

Performance Evaluation of LoRa Communications in Harsh Industrial Environments

An Environment-Aware Adaptive Data-Gathering Method for Packet-Level Index Modulation in LPWA

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