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Comparative Analysis of End Device and Field Test Device Measurements for RSSI, SNR and SF Performance Parameters in an Indoor LoRaWAN Network

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Abstract

Internet of things phenomenon has brought up distinctive technologies that are using wireless communication and appearing in smart city applications. Long range (LoRa) modulation technique has pulled up the market and forced the announcement of LoRa wide area network (LoRaWAN) standard in 2021 by ITU-T with Y.4480 standard code. LoRaWAN is a medium access control protocol using low power wide area network approaches with the aim of long-range coverage and management of many end devices. LoRaWAN networks are emerging all over the world with some existing optimization, planning and network allocation problems that need to be overcome. This paper focuses on comparative analysis and interpretation of measurements performed in a LoRaWAN network deployed in an 18-floor building with a LoRaWAN gateway on the roof. The research covers results of comparative measurements between end device and Adeunis field test device (AFTD) for received signal strength indicator (RSSI), signal-to-noise ratio (SNR) and spreading factor (SF). End devices have been randomly selected from 18th, 12th, 6th and 1st floors and their daily performance data have been gathered through the network server. AFTD has been used to get 100 sample measurements for each floor. Maximum and average RSSI values obtained from end device measurements are higher than ones measured with AFTD except the case in the 18th floor. Excluding the maximum SNR values at the 1st and the 18th floors, all SNR values measured with AFTD are higher than ones obtained from end device measurements. SF measurements show that higher SF values are more likely to be used with increasing distances to the gateway as expected from the theoretical background.

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Data Availability

The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.

Code Availability

Not applicable for this manuscript.

References

  1. MIT Auto-ID Laboratory. (2023). https://autoid.mit.edu/

  2. Liya, L., & Aswathy, M. (2020). LoRa technology for Internet of Things (IoT): A brief survey. In 2020 Fourth international conference on I-SMAC (IoT in Social, Mobile, M. Analytics and Cloud) (I-SMAC’2020) (pp. 8–13). https://doi.org/10.1109/I-SMAC49090.2020.9243449

  3. What are LoRa and LoRaWAN? (2022). https://www.thethingsnetwork.org/docs/lorawan/what-is-lorawan/

  4. Sundaram, J. P. S., Du, W., & Zhao, Z. (2020). A survey on LoRa networking: Research problems, current solutions and open issues. IEEE Communications Surveys and Tutorials, 22(1), 371–388. https://doi.org/10.1109/COMST.2019.2949598

    Article  Google Scholar 

  5. Tardy, I. C. R., Aakvaag, N., Myhre, B., & Bahr, R. (2017). Comparison of wireless techniques applied to environmental sensor monitoring. SINTEF Report, A27942, pp. 15–16. https://sintef.brage.unit.no/sintef-xmlui/handle/11250/2436270

  6. de Camargo, E. T., Spanhol, F. A., & e Souza, A. R. C. (2021). Deployment of a LoRaWAN network and evaluation of tracking devices in the context of smart cities. Journal of Internet Services and Applications, 12, 8. https://doi.org/10.1186/s13174-021-00138-7

    Article  Google Scholar 

  7. Kim, D. Y., Park, J. B., Shin, J. H., & Kim, J. D. (2017). Design and implementation of object tracking system based on LoRa. In 2017 International conference on information networking (ICOIN’2017) (pp. 463–467). https://doi.org/10.1109/ICOIN.2017.7899535

  8. Zhou, B. (2021). Energy-efficient, environment-aware synchronization and connectivity for the Internet of Things. Ph.D. dissertation, University of Nebraska, Lincoln, Nebraska. https://www.proquest.com/dissertations-theses/energy-efficient-environment-aware/docview/2529979887/se-2

  9. Li, Y., Barthelemy, J., Sun, S., Perez, P., & Moran, B. (2022). Urban vehicle localization in public LoRaWan network. IEEE Internet of Things Journal, 9(12), 10283–10294. https://doi.org/10.1109/JIOT.2021.3121778

    Article  Google Scholar 

  10. Di Renzone, G., Parrino, S., Peruzzi, G., & Pozzebon, A. (2021). LoRaWAN in motion: Preliminary tests for real time low power data gathering from vehicles. In 2021 IEEE international workshop on metrology for automotive (MetroAutomotive’2021) (pp. 232–236). https://doi.org/10.1109/MetroAutomotive50197.2021.9502882

  11. Zhuang, Y. (2019). Wireless parking detection system based on sensor fusion and IoT communication. M.Sc. Thesis, University of Washington. https://www.proquest.com/dissertations-theses/wireless-parking-detection-system-based-on-sensor/docview/2305852659/se-2

  12. Kantilal, B. V. (2021). IoT based air quality monitoring system with power consumption optimization and air quality parameters prediction using deep learning. Ph.D. dissertation, The Maharaja Sayajirad University of Baroda. https://www.proquest.com/dissertations-theses/iot-based-air-quality-monitoring-system-with/docview/2647209830/se-2

  13. Abreu, A., Lopes, S. I., Manso, V., & Curado, A. (2020). Low-cost LoRa-based IoT edge device for indoor air quality management in schools. In 2020 International summit smart city 360° (SmartCity 360°’2020) (pp. 246–258). https://doi.org/10.1007/978-3-030-76063-2_18

  14. Ajayi, O. O., Bagula, A. B., Maluleke, H. C., Gaffoor, Z., Jovanovic, N., & Pietersen, K. C. (2022). WaterNet: A network for monitoring and assessing water quality for drinking and irrigation purposes. IEEE Access, 10, 48318–48337. https://doi.org/10.1109/ACCESS.2022.3172274

    Article  Google Scholar 

  15. Brindha, S., Abirami, P., Srikanth, V. P., Raj, A. A., & Raja, K. K. (2019). Efficient water management using LoRa in advance IoT. International Journal of Research in Engineering, Science and Management, 2(3), 834–837.

    Google Scholar 

  16. Zhao, G., Lin, K., & Hao, T. (2023). A feasibility study of LoRaWAN-based wireless underground sensor networks for underground monitoring. Computer Networks, 232, 109851. https://doi.org/10.1016/j.comnet.2023.109851

    Article  Google Scholar 

  17. Adi, P. D. P., & Wahyu, Y. (2023). The error rate analyze and parameter measurement on LoRa communication for health monitoring. Microprocessors and Microsystems, 98, 104820. https://doi.org/10.1016/j.micpro.2023.104820

    Article  Google Scholar 

  18. Santana, J. R., Stores, P., Pérez, J., Sánchez, L., Lanza, J., & Muñoz, L. (2023). Assessing LoRaWAN radio propagation for smart parking service: An experimental study. Computer Networks, 235, 109962. https://doi.org/10.1016/j.comnet.2023.109962

    Article  Google Scholar 

  19. Yasmin, R., Petäjäjärvi, J., Mikhaylov, K., & Pouttu, A. (2018). Large and dense LoRaWAN deployment to monitor real estate conditions and utilization rate. In 2018 IEEE 29th annual international symposium on personal indoor and mobile radio communications (PIMRC’2018) (pp. 1–6). https://doi.org/10.1109/PIMRC.2018.8580985

  20. Parri, L., Parrino, S., Peruzzi, G., & Pozzebon, A. (2021). Offshore LoRaWAN networking: Transmission performances analysis under different environmental conditions. IEEE Transactions on Instrumentation and Measurement, 70, 1–10, Art no. 9507710. https://doi.org/10.1109/TIM.2020.3031193

  21. To, T. H., & Duda, A. (2018). Simulation of LoRa in NS-3: Improving LoRa performance with CSMA. In 2018 IEEE international conference on communications (ICC’2018) (pp. 1–7). https://doi.org/10.1109/ICC.2018.8422800

  22. Ta, D. T., Khawam, K., Lahoud, S., Adjih, C., & Martin, S. (2019). LoRa-MAB: A flexible simulator for decentralized learning resource allocation in IoT networks. In 2022 12th IFIP conference on wireless and mobile networking (WMNC’2019) (pp. 55–62). https://doi.org/10.23919/WMNC.2019.8881393

  23. Citoni, B., Ansari, S., Abbasi, Q. H., Imran, M. A., & Hussain, S. (2022). Comparative analysis of an urban LoRaWAN deployment: Real world versus simulation. IEEE Sensors Journal, 22(17), 17216–17223. https://doi.org/10.1109/JSEN.2022.3193504

    Article  Google Scholar 

  24. Wu, W., Wang, H., & Cheng, Z. (2023). ReLoRaWAN: Reliable data delivery in LoRaWAN networks with multiple gateways. Ad Hoc Networks, 147, 103203. https://doi.org/10.1016/j.adhoc.2023.103203

    Article  Google Scholar 

  25. Adeunis Field Test Device. https://www.adeunis.com/en/produit/ftd-network-tester/

  26. Jeftenić, N., Simić, M., & Stamenković, Z. (2020). Impact of environmental parameters on SNR and RSS in LoRaWAN. In 2020 International conference on electrical, communication, and computer engineering (ICECCE’2020). https://doi.org/10.1109/ICECCE49384.2020.9179250

  27. Montagny S. (2023). LoRa—LoRaWAN and Internet of Things. https://www.univ-smb.fr/lorawan/en/free-book/

  28. Sinha, R. S., Wei, Y., & Hwang, S. H. (2017). A survey on LPWA technology: LoRa and NB-IoT. ICT Express, 3(1), 14–21. https://doi.org/10.1016/j.icte.2017.03.004

    Article  Google Scholar 

  29. Gu, F., Niu, J., Jiang, L., Liu, X., & Atiquzzaman, M. (2020). Survey of the low power wide area network technologies. Journal of Network and Computer Applications, 149, 102459. https://doi.org/10.1016/j.jnca.2019.102459

    Article  Google Scholar 

  30. de Almeida, I. B. F., Chafii, M., Nimr, A., & Fettweis, G. (2021). Alternative chirp spread spectrum techniques for LPWANs. IEEE Transactions on Green Communications and Networking, 5(4), 1846–1855. https://doi.org/10.1109/TGCN.2021.3085477

    Article  Google Scholar 

  31. Adi, P. D. P., Wahyu, Y., & Kitagawa, A. (2022). Analyzes of chirps spread spectrum of ES920LR LoRa 920 MHz. In 2022 11th electrical power, electronics, communications, controls and informatics seminar (EECCIS’2022) (pp. 139–144). https://doi.org/10.1109/EECCIS54468.2022.9902922

  32. Pasolini, G. (2022). On the LoRa chirp spread spectrum modulation: Signal properties and their impact on transmitter and receiver architectures. IEEE Transactions on Wireless Communications, 21(1), 357–369. https://doi.org/10.1109/TWC.2021.3095667

    Article  Google Scholar 

  33. Lopez Chalacan, V. H. L. (2020). Performance evaluation of long range (LoRa) wireless RF technology for the Internet of Things (IoT) using Dragino LoRa at 915 MHz. M.Sc. thesis, University of North Florida. https://www.proquest.com/dissertations-theses/performance-evaluation-long-range-lora-wireless/docview/2519440999/se-2

  34. Spreading Factors. (2022). https://www.thethingsnetwork.org/docs/lorawan/spreading-factors/

  35. Attia, T., Heusse, M., Tourancheau, B., & Duda, A. (2019). Experimental characterization of LoRaWAN link quality. In 2019 IEEE global conference on communications (GLOBECOM’2019). https://doi.org/10.1109/GLOBECOM38437.2019.9013371

  36. LoRa Alliance. (2023). https://lora-alliance.org/

  37. LoRaWAN Architecture. (2023). https://www.thethingsnetwork.org/docs/lorawan/spreading-factors/

  38. Device Classes (2023). https://www.thethingsnetwork.org/docs/lorawan/classes/

  39. Pereira, F., Lopes, S. I., Carvalho, N. B., & Curado, A. (2020). RnProbe: A LoRa-enabled IoT edge device for integrated radon risk management. IEEE Access, 8, 203488–203502. https://doi.org/10.1109/ACCESS.2020.3036980

    Article  Google Scholar 

  40. Peruzzi, G., Pozzebon, A., & Van Der Meer, M. (2023). Fight fire with fire: Detecting forest fires with embedded machine learning models dealing with audio and images on low power IoT devices. Sensors, 23(2), 783. https://doi.org/10.3390/s23020783

    Article  Google Scholar 

  41. Boccadoro, P., Montaruli, B., & Grieco, L. A. (2019). Quakesense, a LoRacompliant earthquake monitoring open system. In 2019 IEEE/ACM 23rd international symposium on distributed simulation and real time applications (DS-RT’2019). https://doi.org/10.1109/DS-RT47707.2019.8958675

  42. Panicker, J. G., Azman, M., & Kashyap, R. (2019). A LoRa wireless mesh network for wide-area animal tracking. In 2019 IEEE international conference on electrical, computer and communication technologies (ICECCT’2019). https://doi.org/10.1109/ICECCT.2019.8868958

  43. Bathre, M., & Das, P. K. (2022). Water supply monitoring system with self-powered LoRa based wireless sensor system powered by solar and hydroelectric energy harvester. Computer Standards and Interfaces, 82, 103630. https://doi.org/10.1016/j.csi.2022.103630

    Article  Google Scholar 

  44. Alghamdi, A. M., Khairullah, E. F., & Al Mojamed, M. M. (2022). LoRaWAN performance analysis for a water monitoring and leakage detection system in a housing complex. Sensors, 22(19), 7188. https://doi.org/10.3390/s22197188

    Article  Google Scholar 

  45. LoRa Physical Layer Packet Format. (2023). https://www.thethingsnetwork.org/docs/lorawan/lora-phy-format/

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Acknowledgements

This research was achieved with the permission of BUSKI (Bursa Metropolitan Municipality Water and Wastewater Management Authority) given in 2021.

Funding

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

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Authors and Affiliations

  1. MSc Program of Electronics Engineering, Graduate School of Natural and Applied Science, Bursa Uludağ University, Bursa, Türkiye

    Ataberk Aksoy

  2. PhD Program of Electronics Engineering, Graduate School of Natural and Applied Science, Bursa Uludağ University, Bursa, Türkiye

    Ömer Yıldız

  3. Department of Electrical and Electronics Engineering, Faculty of Engineering, Bursa Uludağ University, Bursa, Türkiye

    Sait Eser Karlık

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Contributions

AA: Conceptualization, Methodology, Formal Analysis, Investigation, Resources, Data Curation, Visualization, Writing-Original Draft. ÖY: Conceptualization, Methodology, Formal Analysis, Investigation, Resources, Data Curation, Visualization, Writing-Original Draft. SEK: Conceptualization, Methodology, Investigation, Resources, Data Curation, Visualization, Writing-Review and Editing, Supervision, Project Administration.

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Correspondence to Ataberk Aksoy.

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Aksoy, A., Yıldız, Ö. & Karlık, S.E. Comparative Analysis of End Device and Field Test Device Measurements for RSSI, SNR and SF Performance Parameters in an Indoor LoRaWAN Network. Wireless Pers Commun 134, 339–360 (2024). https://doi.org/10.1007/s11277-024-10911-z

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