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LPWAN STANDARTLARI TABANLI BİLİŞSEL RADYO AĞLARI İÇİN SPEKTRUM ALGILAMA YAKLAŞIMI

Year 2021, , 535 - 547, 31.12.2021

Sercan Yalçın

https://doi.org/10.54365/adyumbd.1001507

Abstract

Bilişsel radyo ağları (Cognitive Radio Networks, CRNs) kullanılarak güvenilir bir spektrum elde edebilmek günümüz kablosuz iletişim teknolojileri ve Nesnelerin İnterneti (Internet of Things, IoTs) uygulamaları için vazgeçilmez olmuştur. Bu çalışmada, CRN’ler için spektrum algılama yaklaşımında yeni eğilimler incelenmiştir. Düşük güçlü geniş alan ağları (Low Power Wide Area Networks, LPWANs) standartlarından biri olan geniş kapsama (Long Range, LoRa) içerikli CRN’ler ile spektrum algılaması yapılmıştır. Burada amaçlanan, kullanıcıların frekans spektrumlarından maksimum oranda faydalanabilmesini sağlayabilmektir. Daha hassas spektrum algılaması sayesinde haberleşmedeki farklı bant genişliği ve sinyal yayılım faktörlerine bağlı olarak bant genişliği kullanımı verimli hale getirilmiştir. Buna paralel olarak, bant genişliğinde kullanılan miktar artırılarak verimli güç/frekans analizi yapılmıştır.

Keywords

Düşük güçlü geniş alan ağları (LPWAN) Bilişsel Radyo Ağları Hücresel Ağlar , Hücresel Ağlar Nesnelerin İnterneti

References

  • Mekkia K, Bajica E, Chaxela F, Meyerb F. A comparative study of LPWAN technologies for large-scale IoT deployment. ICT Express 2019; 5(1):1-7.
  • Sanchez-Sutil F, Cano-Ortega A. Smart regulation and efficiency energy system for street lighting with LoRa LPWAN. Sustainable Cities and Society 2021; 70: 102912.
  • Sinha R, Wei Y, Hwang S. A survey on LPWA technology: LoRa and NB-IoT, J. ICT Expr. 2017; 3:14–21.
  • Queralta JP, Giaa TN, Zoub Z, Tenhunenc H, Westerlunda T. Comparative Study of LPWAN Technologies on Unlicensed Bands for M2M Communication in the IoT: beyond LoRa and LoRaWAN. The 14th International Conference on Future Networks and Communications (FNC). August 19-21, Halifax, Canada 2019:343-350.
  • Sumathi AC, Vidhyapriya R, Vivekanandan C, Sangaiah AK. Enhancing 4G Co-existence with Wi-Fi/IoT using Cognitive Radio. Cluster Computing 2019; 22:11295–11305.
  • Onumanyi AJ, Abu-Mahfouz AM, Hancke GP. Low Power Wide Area Network, Cognitive Radio and the Internet of Things: Potentials for Integration. Sensors 2020; 20:6837.
  • MacCartney GR, Rappaport TS. Rural macrocell path loss models for millimeter wave wireless communications. IEEE Journal on Selected Areas in Communications 2017; 35(7):1663–1677.
  • Al-Hourani A, Chandrasekharan S, Kandeepan S. Path loss study for millimeter wave device-to-device communications in urban environment. in 2014 IEEE International Conference on Communications Workshops (ICC) 2014: 102–107.
  • Al-Hourani A. On the probability of line-of-sight in urban environments. IEEE Wireless Communications Letters 2020; 9(8):1178– 1181.
  • SX1276/77/78/79: 137 MHz to 1020 MHz low power long range transceiver, SEMTECH, 2020, [Online]. Available: https://www.semtech.com/ [Erişim: Eylül 2, 2021].
  • Georgiou O, Raza U. Low power wide area network analysis: Can LoRa scale?. IEEE Wireless Communications Letters 2017; 6(2): 162–165.
  • Magrin D, Centenaro M, Vangelista L. Performance evaluation of LoRa networks in a smart city scenario. in 2017 IEEE International Conference on Communications (ICC) 2017: 1–7.
  • Beltramelli L, Mahmood A, Gidlund M, Österberg P, Jennehag U. Interference modelling in a multi-cell LoRa system. in 2018 14th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob) 2018: 1–8.
  • Robyns P, Quax P, Lamotte W, Thenaers, W. A multi-channel software decoder for the lora modulation scheme. in Proceedings of the 3rd International Conference on Internet of Things, Big Data and Security IoTBDS,, INSTICC. SciTePress 2018: 41–51.
  • Knight M, Seeber B. Decoding lora: Realizing a modern lpwan with sdr. Proceedings of the GNU Radio Conference 2016; 1(1).
  • Homssi B, Dakic K, Maselli S, Wolf H, Kandeepan S, Al-Hourani A. IoT Network Design using Open-Source LoRa Coverage Emulator. IEEE Access 2021: 10.1109/ACCESS.2021.DOI.
  • Ruckebusch P, Giannoulis S, Moerman I, Hoebeke J, Poorter E. Modelling the energy consumption for over-the-air software updates in LPWAN networks: SigFox, LoRa and IEEE 802.15.4g. Internet of Things 2018; 3(4): 104-119.
  • LoRa Alliance, “Specification, LoRaWAN,” LoRaWAN, 2018, [Online]. Available: https://lora-alliance.org/sites/default/files/2018- 07/lorawan1.0.3.pdf [Erişim: September 17, 2021].
  • Souza Sant’Ana JM, Hoeller A, Souza RD, Alves H, Montejo-Sánchez S. LoRa performance analysis with superposed signal decoding. IEEE Wireless Communications Letters 2020; 9(11):1865–1868.
  • Beltramelli L, Mahmood A, Osterberg P, Gidlund M. LoRa beyond aloha: An investigation of alternative random access protocols. IEEE Transactions on Industrial Informatics 2020:1–10.
  • Wang YE, Lin X, Grovlen A, Sui Y, Bergman J. A primer on 3GPP narrowband internet of things. IEEE Commun. Mag. 2016; 55 (3): 117– 123.
  • Liberg O, Sundberg M, Wang YPE, Bergman J, Sachs J, Wikström G. Chapter 4 - EC-GSM-IoT performance, Cellular Internet of Things (Second Edition). From Massive Deployments to Critical 5G Applications 2020: 125-154.
  • LoRa Alliance, LoRa modulation basic, and1200.22,(http://www.semtech.com). [Erişim: Ağustos 12, 2021].
  • Cavo L, Fuhrmann S, Liu L. Design of an area efficient crypto processor for 3GPP-LTE NB-IoT devices. Microprocessors and Microsystems 2020; 72: 102899.
  • Sethi A, Jain SK, Vijay S. Secure Self Optimizing Software Defined Framework for NB-IoT Towards 5G. Procedia Computer Science 2020; 171: 2740-2749.
  • Akyildiz IF, Lee WY, Vuran MC, Mohanty S. NeXt Generation/Dynamic Spectrum Access/Cognitive Radio Wireless Networks: A survey. Computer Networks 2006; 50(13): 2127–2159.
  • Rao R, Cheng Q, Kelkar A, Chaudhari D. Cooperative Cognitive Radio Network Testbed. ICST’s Global Community Magazine 2011: ICaST.
  • Akhtar AN, Siddique AM. Spectrum Decision Framework to Support Cognitive Radio Based IoT in 5G. in Cognitive Radio in 4G/5G Wireless Communication Systems Book, 2018.
  • Rateb AM. Introduction to Cognitive Radio Systems. Universiti Teknologi Malaysia, 2008.
  • Almasoud AMM. Robust Provisioning of Multicast Sessions in Cognitive 160 Radio Networks. in Proceeding of the 10th International Wireless Communications and Mobile Computing Conference (IWCMC) 2014:417–422. doi: 10.1109/IWCMC.2014.6906393.
  • Tendeng R, Lee Y, Koo I. Implementation and Measurement of Spectrum Sensing for Cognitive Radio Networks Based on LoRa and GNU Radio. International Journal of Advanced Smart Convergence 2018;7(3): 23-36.
  • Nurelmadina N, Hasan MK, Memon I, Saeed RA, Ariffin KAZ, Ali ES, Mokhtar RA, Islam S, Hossain E, Hassan MA. A Systematic Review on Cognitive Radio in Low Power Wide Area Network for Industrial IoT Applications. Sustainability 2021; 13:1-22.

Year 2021, , 535 - 547, 31.12.2021

Sercan Yalçın

https://doi.org/10.54365/adyumbd.1001507

Abstract

References

  • Mekkia K, Bajica E, Chaxela F, Meyerb F. A comparative study of LPWAN technologies for large-scale IoT deployment. ICT Express 2019; 5(1):1-7.
  • Sanchez-Sutil F, Cano-Ortega A. Smart regulation and efficiency energy system for street lighting with LoRa LPWAN. Sustainable Cities and Society 2021; 70: 102912.
  • Sinha R, Wei Y, Hwang S. A survey on LPWA technology: LoRa and NB-IoT, J. ICT Expr. 2017; 3:14–21.
  • Queralta JP, Giaa TN, Zoub Z, Tenhunenc H, Westerlunda T. Comparative Study of LPWAN Technologies on Unlicensed Bands for M2M Communication in the IoT: beyond LoRa and LoRaWAN. The 14th International Conference on Future Networks and Communications (FNC). August 19-21, Halifax, Canada 2019:343-350.
  • Sumathi AC, Vidhyapriya R, Vivekanandan C, Sangaiah AK. Enhancing 4G Co-existence with Wi-Fi/IoT using Cognitive Radio. Cluster Computing 2019; 22:11295–11305.
  • Onumanyi AJ, Abu-Mahfouz AM, Hancke GP. Low Power Wide Area Network, Cognitive Radio and the Internet of Things: Potentials for Integration. Sensors 2020; 20:6837.
  • MacCartney GR, Rappaport TS. Rural macrocell path loss models for millimeter wave wireless communications. IEEE Journal on Selected Areas in Communications 2017; 35(7):1663–1677.
  • Al-Hourani A, Chandrasekharan S, Kandeepan S. Path loss study for millimeter wave device-to-device communications in urban environment. in 2014 IEEE International Conference on Communications Workshops (ICC) 2014: 102–107.
  • Al-Hourani A. On the probability of line-of-sight in urban environments. IEEE Wireless Communications Letters 2020; 9(8):1178– 1181.
  • SX1276/77/78/79: 137 MHz to 1020 MHz low power long range transceiver, SEMTECH, 2020, [Online]. Available: https://www.semtech.com/ [Erişim: Eylül 2, 2021].
  • Georgiou O, Raza U. Low power wide area network analysis: Can LoRa scale?. IEEE Wireless Communications Letters 2017; 6(2): 162–165.
  • Magrin D, Centenaro M, Vangelista L. Performance evaluation of LoRa networks in a smart city scenario. in 2017 IEEE International Conference on Communications (ICC) 2017: 1–7.
  • Beltramelli L, Mahmood A, Gidlund M, Österberg P, Jennehag U. Interference modelling in a multi-cell LoRa system. in 2018 14th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob) 2018: 1–8.
  • Robyns P, Quax P, Lamotte W, Thenaers, W. A multi-channel software decoder for the lora modulation scheme. in Proceedings of the 3rd International Conference on Internet of Things, Big Data and Security IoTBDS,, INSTICC. SciTePress 2018: 41–51.
  • Knight M, Seeber B. Decoding lora: Realizing a modern lpwan with sdr. Proceedings of the GNU Radio Conference 2016; 1(1).
  • Homssi B, Dakic K, Maselli S, Wolf H, Kandeepan S, Al-Hourani A. IoT Network Design using Open-Source LoRa Coverage Emulator. IEEE Access 2021: 10.1109/ACCESS.2021.DOI.
  • Ruckebusch P, Giannoulis S, Moerman I, Hoebeke J, Poorter E. Modelling the energy consumption for over-the-air software updates in LPWAN networks: SigFox, LoRa and IEEE 802.15.4g. Internet of Things 2018; 3(4): 104-119.
  • LoRa Alliance, “Specification, LoRaWAN,” LoRaWAN, 2018, [Online]. Available: https://lora-alliance.org/sites/default/files/2018- 07/lorawan1.0.3.pdf [Erişim: September 17, 2021].
  • Souza Sant’Ana JM, Hoeller A, Souza RD, Alves H, Montejo-Sánchez S. LoRa performance analysis with superposed signal decoding. IEEE Wireless Communications Letters 2020; 9(11):1865–1868.
  • Beltramelli L, Mahmood A, Osterberg P, Gidlund M. LoRa beyond aloha: An investigation of alternative random access protocols. IEEE Transactions on Industrial Informatics 2020:1–10.
  • Wang YE, Lin X, Grovlen A, Sui Y, Bergman J. A primer on 3GPP narrowband internet of things. IEEE Commun. Mag. 2016; 55 (3): 117– 123.
  • Liberg O, Sundberg M, Wang YPE, Bergman J, Sachs J, Wikström G. Chapter 4 - EC-GSM-IoT performance, Cellular Internet of Things (Second Edition). From Massive Deployments to Critical 5G Applications 2020: 125-154.
  • LoRa Alliance, LoRa modulation basic, and1200.22,(http://www.semtech.com). [Erişim: Ağustos 12, 2021].
  • Cavo L, Fuhrmann S, Liu L. Design of an area efficient crypto processor for 3GPP-LTE NB-IoT devices. Microprocessors and Microsystems 2020; 72: 102899.
  • Sethi A, Jain SK, Vijay S. Secure Self Optimizing Software Defined Framework for NB-IoT Towards 5G. Procedia Computer Science 2020; 171: 2740-2749.
  • Akyildiz IF, Lee WY, Vuran MC, Mohanty S. NeXt Generation/Dynamic Spectrum Access/Cognitive Radio Wireless Networks: A survey. Computer Networks 2006; 50(13): 2127–2159.
  • Rao R, Cheng Q, Kelkar A, Chaudhari D. Cooperative Cognitive Radio Network Testbed. ICST’s Global Community Magazine 2011: ICaST.
  • Akhtar AN, Siddique AM. Spectrum Decision Framework to Support Cognitive Radio Based IoT in 5G. in Cognitive Radio in 4G/5G Wireless Communication Systems Book, 2018.
  • Rateb AM. Introduction to Cognitive Radio Systems. Universiti Teknologi Malaysia, 2008.
  • Almasoud AMM. Robust Provisioning of Multicast Sessions in Cognitive 160 Radio Networks. in Proceeding of the 10th International Wireless Communications and Mobile Computing Conference (IWCMC) 2014:417–422. doi: 10.1109/IWCMC.2014.6906393.
  • Tendeng R, Lee Y, Koo I. Implementation and Measurement of Spectrum Sensing for Cognitive Radio Networks Based on LoRa and GNU Radio. International Journal of Advanced Smart Convergence 2018;7(3): 23-36.
  • Nurelmadina N, Hasan MK, Memon I, Saeed RA, Ariffin KAZ, Ali ES, Mokhtar RA, Islam S, Hossain E, Hassan MA. A Systematic Review on Cognitive Radio in Low Power Wide Area Network for Industrial IoT Applications. Sustainability 2021; 13:1-22.
There are 32 citations in total.

Details

Primary Language Turkish
Subjects Engineering
Journal Section Makaleler
Authors

Sercan Yalçın 0000-0003-1420-2490

Publication Date December 31, 2021
Submission Date September 27, 2021
Published in Issue Year 2021

Cite

APA Yalçın, S. (2021). LPWAN STANDARTLARI TABANLI BİLİŞSEL RADYO AĞLARI İÇİN SPEKTRUM ALGILAMA YAKLAŞIMI. Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi, 8(15), 535-547. https://doi.org/10.54365/adyumbd.1001507
AMA Yalçın S. LPWAN STANDARTLARI TABANLI BİLİŞSEL RADYO AĞLARI İÇİN SPEKTRUM ALGILAMA YAKLAŞIMI. Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi. December 2021;8(15):535-547. doi:10.54365/adyumbd.1001507
Chicago Yalçın, Sercan. “LPWAN STANDARTLARI TABANLI BİLİŞSEL RADYO AĞLARI İÇİN SPEKTRUM ALGILAMA YAKLAŞIMI”. Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi 8, no. 15 (December 2021): 535-47. https://doi.org/10.54365/adyumbd.1001507.
EndNote Yalçın S (December 1, 2021) LPWAN STANDARTLARI TABANLI BİLİŞSEL RADYO AĞLARI İÇİN SPEKTRUM ALGILAMA YAKLAŞIMI. Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi 8 15 535–547.
IEEE S. Yalçın, “LPWAN STANDARTLARI TABANLI BİLİŞSEL RADYO AĞLARI İÇİN SPEKTRUM ALGILAMA YAKLAŞIMI”, Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi, vol. 8, no. 15, pp. 535–547, 2021, doi: 10.54365/adyumbd.1001507.
ISNAD Yalçın, Sercan. “LPWAN STANDARTLARI TABANLI BİLİŞSEL RADYO AĞLARI İÇİN SPEKTRUM ALGILAMA YAKLAŞIMI”. Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi 8/15 (December 2021), 535-547. https://doi.org/10.54365/adyumbd.1001507.
JAMA Yalçın S. LPWAN STANDARTLARI TABANLI BİLİŞSEL RADYO AĞLARI İÇİN SPEKTRUM ALGILAMA YAKLAŞIMI. Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi. 2021;8:535–547.
MLA Yalçın, Sercan. “LPWAN STANDARTLARI TABANLI BİLİŞSEL RADYO AĞLARI İÇİN SPEKTRUM ALGILAMA YAKLAŞIMI”. Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi, vol. 8, no. 15, 2021, pp. 535-47, doi:10.54365/adyumbd.1001507.
Vancouver Yalçın S. LPWAN STANDARTLARI TABANLI BİLİŞSEL RADYO AĞLARI İÇİN SPEKTRUM ALGILAMA YAKLAŞIMI. Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi. 2021;8(15):535-47.