Study of LoRaWAN Performance Under a Noisy Industrial Channel

Bahri, Nisrine; Saadaoui, Safa; Tabaa, Mohamed; Sadik, Mohamed; Medromi, Hicham

doi:10.1007/978-981-16-5559-3_38

Cited by 3 publications

(1 citation statement)

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“…However, industrial environments are often noisy, with sources of electromagnetic noise such as electronic equipment, communications equipment, and heavy machinery, which can have a negative impact on the performance of this technology [22]. Studies have been carried out to assess LoRa's performance in these environments, such as the work in [23], whose authors examined the effect of industrial and AWGN noise on LoRa communication systems. The results showed a significant degradation in signal quality in the presence of impulse noise compared with Gaussian noise, with BER values ranging from 10 −2 to 10 −3 for both types of noise.…”

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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Section: Related Workmentioning

confidence: 99%