Araştırma Makalesi
BibTex RIS Kaynak Göster

Regression Analysis of SNR and RSSI Relation in an Indoor LoRaWAN Network with MATLAB Curve Fitting Method

Yıl 2025, Cilt: 15 Sayı: 2, 702 - 717, 15.06.2025

Ömer Yildiz , Sait Eser Karlık

https://doi.org/10.31466/kfbd.1577612

Öz

Today, cities are growing rapidly. While increasing population reveals the requirement for more efficient use of resources in urban centers; this situation has brought along concepts of smart city and internet of things. Internet of things applications, which enable resource management, tracking, performance analysis and optimization with low-cost, wireless and remote data exchange in living spaces, bring us LoRaWAN. LoRaWAN technology has become widespread thanks to its low infrastructure cost, low battery consumption, easy installation and expandable network structure in long haul communication. In LoRaWAN network planning, RSSI, SNR and SF values are important for network efficiency. In this study, the relation between SNR and RSSI is analyzed using data obtained from an indoor LoRaWAN network and MATLAB curve fitting method. In curve fitting, polynomial, Fourier and Gaussian regression models are analyzed. In terms of goodness-of-fit parameters, it is observed that the equation of the curve with the highest fit to the network data can be obtained with a 9th order polynomial. When the goodness-of-fit comparison of curves fitted to the network data in order to define the relation between SNR and RSSI for the case where the SF parameter is constant at SF7 is made, the R2 value is determined as 0.9362 when polynomial regression model is used, as 0.8459 when Fourier regression model is used, and as 0.8572 when Gaussian regression model is used. RMSE values are found as 0.2440 in polynomial regression model, 0.3895 in Fourier regression model and 0.3828 in Gaussian regression model.

Anahtar Kelimeler

LoRaWAN RSSI SNR SF Curve fitting

Proje Numarası

FGA-2023-1297

Kaynakça

  • Ahmed, S. T., ve Annamalai, A., (2023, Mayıs). Improving Geo-Location Performance of LoRa with Adaptive Spreading Factor, 2023 IEEE 13th Symposium on Computer Applications & Industrial Electronics (ISCAIE), (s. 386-391), Penang, Malaysia. https://doi.org/10.1109/ISCAIE57739.2023.10165296
  • Alipio, M., ve Bures, M., (2024). Current testing and performance evaluation methodologies of LoRa and LoRaWAN in IoT applications: Classification, issues, and future directives, Internet of Things, 25, 101053. https://doi.org/10.1016/j.iot.2023.101053
  • Alkhazmi, E. H., Elkawafi, S. M, Aldarrat, A. A., Abbas, M. A., Abubakr, H., ve Shamatah, H.A., (2023, Aralık). Analysis of Real-World LoRaWAN Network Performance Across Outdoor and Indoor Scenarios, 2023 IEEE 11th International Conference on Systems and Control (ICSC), (s. 329-334), Sousse, Tunisia. https://doi.org/10.1109/ICSC58660.2023.10449775
  • Chaudhari, B., ve Zennaro, M., (2020). LPWAN technologies for IoT and M2M applications: Introduction to low-power wide-area networks. Elsevier Inc. Academic Press.
  • Damayanti, S. D., Suryanegara M. ve Hayati N., (2024, Temmuz). LoRaWAN for Underwater System: Early Results from Performance Testing on the Swimming Pool, 2024 7th International Conference on Communication Engineering and Technology (ICCET), (s. 47-53), Tokyo, Japan. https://doi.org/10.1109/ICCET62255.2024.00015
  • Kaur, G., Balyan, V., Gupta, S.H., (2024). Experimental analysis of low-duty cycle campus deployed IoT network using LoRa technology, Results in Engineering, 23, 102844. https://doi.org/10.1016/j.rineng.2024.102844.
  • Lee, S., Lee, J., Park, H.-S., ve Choi, J.-K., (2021). A novel fair and scalable relay control scheme for Internet of Things in LoRa-based low-power wide-area networks. IEEE Internet of Things Journal, 8(7), 5985-6001. https://doi.org/10.1109/JIOT.2020.3034185
  • Moradbeikie, A., Keshavarz, A., Rostami, H., Paiva, S., ve Lopes, S. I., (2023). A cost-effective LoRaWAN-based IoT localization method using fixed reference nodes and dual-slope path-loss modeling, Internet of Things, 24, 100990. https://doi.org/10.1016/j.iot.2023.100990
  • Newman, D., (2019). Return on IoT: Dealing with the IoT skills gap, Retrieved from Forbes Web site: https://www.forbes.com/sites/danielnewman/2019/07/30/return-on-iot-dealing-with-the-iot-skills-gap/
  • Purnama, A. A. F., ve Nashiruddin, M. I., (2019, Aralık). Designing LoRaWAN Internet of Things Network for Advanced Metering Infrastructure (AMI) in Surabaya and Its Surrounding Cities, 2019 International Seminar on Research of Information Technology and Intelligent Systems (ISRITI), (s. 194-199) Yogyakarta, Indonesia. https://doi.org/10.1109/ISRITI48646.2019.9034571
  • Silveira, J. D. F., Veloso, A. F. da S., Júnior, J. V. dos R., Soares, A. C. B., ve Rabêlo, R. A. L., (2021, Ekim). A New Low-Cost LoRaWAN Power Switch for Smart Farm Applications, 2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC), (s. 3330-3335) Melbourne, Australia. https://doi.org/10.1109/SMC52423.2021.9659076
  • Santana, J. R., Sotres, 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
  • Sharma, A., Kapoor, D. S., Nayyar, A., Qureshi, B., Singh, K. J., ve Thakur, K., (2022). Exploration of IoT nodes communication using LoRaWAN in forest environment, Computers, Materials and Continua, 71(3), 6239-6256. https://doi.org/10.32604/cmc.2022.024639.
  • URL-1:Internet Engineering Task Force (IETF), Low-power wide area network (LPWAN) overview, 2018. https://datatracker.ietf.org/doc/html/rfc8376, (Erişim Tarihi: 15 Ekim 2024).
  • URL-2: LoRa Alliance® achieves 66% growth in public LoRaWAN® networks over past 3 years, LoRa Alliance®, 2022. https://resources.lora-alliance.org/home/lora-alliance-achieves-66-growth-in-public-lorawan-networks-over-past-3-years, (Erişim Tarihi:15 Ekim 2024).
  • URL-3: ITU-T Y.4480 (11/2021), Low power protocol for wide area wireless networks. https://www.itu.int/rec/T-REC-Y.4480-202111-I, (Erişim Tarihi: 15 Ekim 2024).
  • URL-4: LoRa: Kablosuz Haberleşmenin Yükselen Yıldızı. https://gsl.com.tr/lora-kablosuz-haberlesmenin-yukselen-yildizi.html, (Erişim Tarihi:15 Ekim 2024)
  • URL-5: LoRaWAN® network architecture. https://lora-alliance.org/about-lorawan/, (Erişim Tarihi: 15 Ekim 2024).
  • URL-6: Skysens motion acceleration monitoring device. https://store.gsl.com.tr/class/INNOVAEditor/assets/Motion_Module_SKYMOT1_ACC_Datasheet_v104.pdf, (Erişim Tarihi: 15 Ekim 2024).
  • URL-7: RN2483 Low-power long range LoRa® technology transceiver module, Microchip Corporation. https://ww1.microchip.com/downloads/aemDocuments/documents/OTH/ProductDocuments/DataSheets/RN2483-Low-Power-Long-Range-LoRa-Technology-Transceiver-Module-DS50002346F.pdf, (Erişim Tarihi: 15 Ekim 2024).
  • URL-8: RAK7246G WisGate Developer D0 Gateway Datasheet. https://docs.rakwireless.com/Product-Categories/WisGate/RAK7246G/Datasheet/, (Erişim Tarihi: 15 Ekim 2024).
  • URL-9: The Things Network. https://www.thethingsnetwork.org/, (Erişim Tarihi: 15 Ekim 2024).
  • URL-10: Curve fitting toolbox. https://www.mathworks.com/help/curvefit/index.html?s_tid=CRUX_lftnav, (Erişim Tarihi: 15 Ekim 2024).
  • URL-11: Goodness of fit. https://www.mathworks.com/help/ident/ref/goodnessoffit.html?s_tid=doc_ta, (Erişim Tarihi: 15 Ekim 2024).
  • URL-12: RMSE. https://www.mathworks.com/help/matlab/ref/rmse.html?s_tid=doc_ta, (Erişim Tarihi: 15 Ekim 2024).
  • URL-13: Evaluating goodness of fit. https://www.mathworks.com/help/curvefit/evaluating-goodness-of-fit.html, (Erişim Tarihi: 15 Ekim 2024).

Bir Bina İçi LoRaWAN Ağında SNR ile RSSI İlişkisinin MATLAB Eğri Uydurma Yöntemi Yardımıyla Regresyon Analizi

Yıl 2025, Cilt: 15 Sayı: 2, 702 - 717, 15.06.2025

Ömer Yildiz , Sait Eser Karlık

https://doi.org/10.31466/kfbd.1577612

Öz

Günümüzde şehirler hızla büyümektedir. Artan nüfus, kent merkezlerindeki kaynakların daha verimli kullanılması gerekliliğini ortaya çıkarırken; bu durum akıllı şehir ve nesnelerin interneti kavramlarını beraberinde getirmiştir. Yaşam alanlarında düşük maliyetli, kablosuz ve uzaktan veri alışverişi ile kaynak yönetimi, takibi, performans analizi ve optimizasyonu yapmaya imkân sağlayan nesnelerin interneti uygulamaları, LoRaWAN’ı karşımıza çıkarmaktadır. LoRaWAN teknolojisi, uzak mesafe iletişimde düşük altyapı maliyeti, düşük pil tüketimi, kolay kurulum ve genişleyebilir ağ yapısı özelliği sayesinde yaygınlaşmıştır. LoRaWAN ağ planlamasında, RSSI, SNR ve SF değerleri ağ verimliliği için önem arz eder. Bu çalışmada, bir bina içi LoRaWAN ağından elde edilen veriler ve MATLAB eğri uydurma yöntemi kullanılarak SNR ile RSSI ilişkisinin analizi gerçekleştirilmiştir. Eğri uydurmada, polinom, Fourier ve Gauss regresyon modelleri incelenmiştir. Uyum iyiliği parametreleri açısından, ağ verilerine en yüksek uyumu sağlayan eğrinin denkleminin 9. dereceden bir polinom ile ifade edilebildiği gözlenmiştir. SF parametresinin SF7 değerinde sabit olduğu durumda, SNR ile RSSI arasındaki ilişkiyi tanımlamak için ağ verilerine uydurulan eğrilerin uyum iyiliği karşılaştırması yapıldığında; R2 değeri, polinom regresyon modeli kullanıldığında 0.9362, Fourier regresyon modeli kullanıldığında 0.8459, Gauss regresyon modeli kullanıldığında ise 0.8572 olarak belirlenmiştir. RMSE değerleri ise, polinom regresyon modelinde 0.2440, Fourier regresyon modelinde 0.3895 ve Gauss regresyon modelinde 0.3828 olarak bulunmuştur.

Anahtar Kelimeler

LoRaWAN RSSI SNR SF Eğri uydurma

Etik Beyan

Yapılan çalışmada araştırma ve yayın etiğine uyulmuştur.

Destekleyen Kurum

BURSA ULUDAĞ ÜNİVERSİTESİ

Proje Numarası

FGA-2023-1297

Teşekkür

Bu çalışma, Bursa Uludağ Üniversitesi Bilimsel Araştırma Projeleri (BAP) Koordinatörlüğü tarafından, FGA-2023-1297 numaralı proje kapsamında desteklenmiştir.

Kaynakça

  • Ahmed, S. T., ve Annamalai, A., (2023, Mayıs). Improving Geo-Location Performance of LoRa with Adaptive Spreading Factor, 2023 IEEE 13th Symposium on Computer Applications & Industrial Electronics (ISCAIE), (s. 386-391), Penang, Malaysia. https://doi.org/10.1109/ISCAIE57739.2023.10165296
  • Alipio, M., ve Bures, M., (2024). Current testing and performance evaluation methodologies of LoRa and LoRaWAN in IoT applications: Classification, issues, and future directives, Internet of Things, 25, 101053. https://doi.org/10.1016/j.iot.2023.101053
  • Alkhazmi, E. H., Elkawafi, S. M, Aldarrat, A. A., Abbas, M. A., Abubakr, H., ve Shamatah, H.A., (2023, Aralık). Analysis of Real-World LoRaWAN Network Performance Across Outdoor and Indoor Scenarios, 2023 IEEE 11th International Conference on Systems and Control (ICSC), (s. 329-334), Sousse, Tunisia. https://doi.org/10.1109/ICSC58660.2023.10449775
  • Chaudhari, B., ve Zennaro, M., (2020). LPWAN technologies for IoT and M2M applications: Introduction to low-power wide-area networks. Elsevier Inc. Academic Press.
  • Damayanti, S. D., Suryanegara M. ve Hayati N., (2024, Temmuz). LoRaWAN for Underwater System: Early Results from Performance Testing on the Swimming Pool, 2024 7th International Conference on Communication Engineering and Technology (ICCET), (s. 47-53), Tokyo, Japan. https://doi.org/10.1109/ICCET62255.2024.00015
  • Kaur, G., Balyan, V., Gupta, S.H., (2024). Experimental analysis of low-duty cycle campus deployed IoT network using LoRa technology, Results in Engineering, 23, 102844. https://doi.org/10.1016/j.rineng.2024.102844.
  • Lee, S., Lee, J., Park, H.-S., ve Choi, J.-K., (2021). A novel fair and scalable relay control scheme for Internet of Things in LoRa-based low-power wide-area networks. IEEE Internet of Things Journal, 8(7), 5985-6001. https://doi.org/10.1109/JIOT.2020.3034185
  • Moradbeikie, A., Keshavarz, A., Rostami, H., Paiva, S., ve Lopes, S. I., (2023). A cost-effective LoRaWAN-based IoT localization method using fixed reference nodes and dual-slope path-loss modeling, Internet of Things, 24, 100990. https://doi.org/10.1016/j.iot.2023.100990
  • Newman, D., (2019). Return on IoT: Dealing with the IoT skills gap, Retrieved from Forbes Web site: https://www.forbes.com/sites/danielnewman/2019/07/30/return-on-iot-dealing-with-the-iot-skills-gap/
  • Purnama, A. A. F., ve Nashiruddin, M. I., (2019, Aralık). Designing LoRaWAN Internet of Things Network for Advanced Metering Infrastructure (AMI) in Surabaya and Its Surrounding Cities, 2019 International Seminar on Research of Information Technology and Intelligent Systems (ISRITI), (s. 194-199) Yogyakarta, Indonesia. https://doi.org/10.1109/ISRITI48646.2019.9034571
  • Silveira, J. D. F., Veloso, A. F. da S., Júnior, J. V. dos R., Soares, A. C. B., ve Rabêlo, R. A. L., (2021, Ekim). A New Low-Cost LoRaWAN Power Switch for Smart Farm Applications, 2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC), (s. 3330-3335) Melbourne, Australia. https://doi.org/10.1109/SMC52423.2021.9659076
  • Santana, J. R., Sotres, 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
  • Sharma, A., Kapoor, D. S., Nayyar, A., Qureshi, B., Singh, K. J., ve Thakur, K., (2022). Exploration of IoT nodes communication using LoRaWAN in forest environment, Computers, Materials and Continua, 71(3), 6239-6256. https://doi.org/10.32604/cmc.2022.024639.
  • URL-1:Internet Engineering Task Force (IETF), Low-power wide area network (LPWAN) overview, 2018. https://datatracker.ietf.org/doc/html/rfc8376, (Erişim Tarihi: 15 Ekim 2024).
  • URL-2: LoRa Alliance® achieves 66% growth in public LoRaWAN® networks over past 3 years, LoRa Alliance®, 2022. https://resources.lora-alliance.org/home/lora-alliance-achieves-66-growth-in-public-lorawan-networks-over-past-3-years, (Erişim Tarihi:15 Ekim 2024).
  • URL-3: ITU-T Y.4480 (11/2021), Low power protocol for wide area wireless networks. https://www.itu.int/rec/T-REC-Y.4480-202111-I, (Erişim Tarihi: 15 Ekim 2024).
  • URL-4: LoRa: Kablosuz Haberleşmenin Yükselen Yıldızı. https://gsl.com.tr/lora-kablosuz-haberlesmenin-yukselen-yildizi.html, (Erişim Tarihi:15 Ekim 2024)
  • URL-5: LoRaWAN® network architecture. https://lora-alliance.org/about-lorawan/, (Erişim Tarihi: 15 Ekim 2024).
  • URL-6: Skysens motion acceleration monitoring device. https://store.gsl.com.tr/class/INNOVAEditor/assets/Motion_Module_SKYMOT1_ACC_Datasheet_v104.pdf, (Erişim Tarihi: 15 Ekim 2024).
  • URL-7: RN2483 Low-power long range LoRa® technology transceiver module, Microchip Corporation. https://ww1.microchip.com/downloads/aemDocuments/documents/OTH/ProductDocuments/DataSheets/RN2483-Low-Power-Long-Range-LoRa-Technology-Transceiver-Module-DS50002346F.pdf, (Erişim Tarihi: 15 Ekim 2024).
  • URL-8: RAK7246G WisGate Developer D0 Gateway Datasheet. https://docs.rakwireless.com/Product-Categories/WisGate/RAK7246G/Datasheet/, (Erişim Tarihi: 15 Ekim 2024).
  • URL-9: The Things Network. https://www.thethingsnetwork.org/, (Erişim Tarihi: 15 Ekim 2024).
  • URL-10: Curve fitting toolbox. https://www.mathworks.com/help/curvefit/index.html?s_tid=CRUX_lftnav, (Erişim Tarihi: 15 Ekim 2024).
  • URL-11: Goodness of fit. https://www.mathworks.com/help/ident/ref/goodnessoffit.html?s_tid=doc_ta, (Erişim Tarihi: 15 Ekim 2024).
  • URL-12: RMSE. https://www.mathworks.com/help/matlab/ref/rmse.html?s_tid=doc_ta, (Erişim Tarihi: 15 Ekim 2024).
  • URL-13: Evaluating goodness of fit. https://www.mathworks.com/help/curvefit/evaluating-goodness-of-fit.html, (Erişim Tarihi: 15 Ekim 2024).
Toplam 26 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Elektronik Cihaz ve Sistem Performansı Değerlendirme, Test ve Simülasyon, Elektronik, Sensörler ve Dijital Donanım (Diğer)
Bölüm Makaleler
Yazarlar

Ömer Yildiz 0000-0002-4702-0469

Sait Eser Karlık 0000-0001-5985-210X

Proje Numarası FGA-2023-1297
Yayımlanma Tarihi 15 Haziran 2025
Gönderilme Tarihi 1 Kasım 2024
Kabul Tarihi 26 Mart 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 15 Sayı: 2

Kaynak Göster

APA Yildiz, Ö., & Karlık, S. E. (2025). Bir Bina İçi LoRaWAN Ağında SNR ile RSSI İlişkisinin MATLAB Eğri Uydurma Yöntemi Yardımıyla Regresyon Analizi. Karadeniz Fen Bilimleri Dergisi, 15(2), 702-717. https://doi.org/10.31466/kfbd.1577612
 Kapak Resmi İndir

by-nc-sa.pngThis work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.