This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
K. Mekki, E. Bajic, F. Chaxel, and F. Meyer, “A comparative study of LPWAN technologies for large-scale IoT deployment,” ICT Express, vol. 5, no. 1, 2019, doi: 10.1016/j.icte.2017.12.005.MekkiK.BajicE.ChaxelF.MeyerF.“A comparative study of LPWAN technologies for large-scale IoT deployment,”ICT Express51201910.1016/j.icte.2017.12.005Open DOISearch in Google Scholar
F. Sanchez-Sutil and A. Cano-Ortega, “Smart regulation and efficiency energy system for street lighting with LoRa LPWAN,” Sustain Cities Soc, vol. 70, 2021, doi: 10.1016/j.scs.2021.102912.Sanchez-SutilF.Cano-OrtegaA.“Smart regulation and efficiency energy system for street lighting with LoRa LPWAN,”Sustain Cities Soc70202110.1016/j.scs.2021.102912Open DOISearch in Google Scholar
G. Gupta and R. Van Zyl, “Energy harvested end nodes and performance improvement of LoRa networks,” International Journal on Smart Sensing and Intelligent Systems, vol. 14, no. 1, 2021, doi: 10.21307/IJSSIS-2021-002.GuptaG.Van ZylR.“Energy harvested end nodes and performance improvement of LoRa networks,”International Journal on Smart Sensing and Intelligent Systems141202110.21307/IJSSIS-2021-002Open DOISearch in Google Scholar
R. S. Sinha, Y. Wei, and S. H. Hwang, “A survey on LPWA technology: LoRa and NB-IoT,” ICT Express, vol. 3, no. 1. 2017. doi: 10.1016/j.icte.2017.03.004.SinhaR. S.WeiY.HwangS. H.“A survey on LPWA technology: LoRa and NB-IoT,”ICT Express31201710.1016/j.icte.2017.03.004Open DOISearch in Google Scholar
J. Peña Queralta, T. N. Gia, Z. Zou, H. Tenhunen, and T. Westerlund, “Comparative study of LPWAN technologies on unlicensed bands for M2M communication in the IoT: Beyond Lora and Lorawan,” in Procedia Computer Science, 2019. doi: 10.1016/j.procs.2019.08.049.Peña QueraltaJ.GiaT. N.ZouZ.TenhunenH.WesterlundT.“Comparative study of LPWAN technologies on unlicensed bands for M2M communication in the IoT: Beyond Lora and Lorawan,”inProcedia Computer Science201910.1016/j.procs.2019.08.049Open DOISearch in Google Scholar
G. Gupta and R. Van Zyl, “NOMA-Based LPWA Networks,” in Lecture Notes in Networks and Systems, 2022. doi: 10.1007/978-981-16-2126-0_42.GuptaG.Van ZylR.“NOMA-Based LPWA Networks,”inLecture Notes in Networks and Systems202210.1007/978-981-16-2126-0_42Open DOISearch in Google Scholar
G. Gupta, R. Van Zyl, and V. Balyan, “Evaluation of LoRa nodes for long-range communication,” Nonlinear Engineering, vol. 11, no. 1, 2022, doi: 10.1515/nleng-2022-0236.GuptaG.Van ZylR.BalyanV.“Evaluation of LoRa nodes for long-range communication,”Nonlinear Engineering111202210.1515/nleng-2022-0236Open DOISearch in Google Scholar
A. J. Onumanyi, A. M. Abu-Mahfouz, and G. P. Hancke, “Low power wide area network, cognitive radio and the internet of things: Potentials for integration,” Sensors (Switzerland), vol. 20, no. 23. 2020. doi: 10.3390/s20236837.OnumanyiA. J.Abu-MahfouzA. M.HanckeG. P.“Low power wide area network, cognitive radio and the internet of things: Potentials for integration,”Sensors (Switzerland)2023202010.3390/s20236837Open DOISearch in Google Scholar
A. C. Sumathi, R. Vidhyapriya, C. Vivekanandan, and A. K. Sangaiah, “Enhancing 4G Co-existence with Wi-Fi/IoT using cognitive radio,” Cluster Comput, vol. 22, 2019, doi: 10.1007/s10586-017-1383-5.SumathiA. C.VidhyapriyaR.VivekanandanC.SangaiahA. K.“Enhancing 4G Co-existence with Wi-Fi/IoT using cognitive radio,”Cluster Comput22201910.1007/s10586-017-1383-5Open DOISearch in Google Scholar
L. Beltramelli, A. Mahmood, M. Gidlund, P. Osterberg, and U. Jennehag, “Interference Modelling in a Multi-Cell LoRa System,” in International Conference on Wireless and Mobile Computing, Networking and Communications, 2018. doi: 10.1109/WiMOB.2018.8589100.BeltramelliL.MahmoodA.GidlundM.OsterbergP.JennehagU.“Interference Modelling in a Multi-Cell LoRa System,”inInternational Conference on Wireless and Mobile Computing, Networking and Communications201810.1109/WiMOB.2018.8589100Open DOISearch in Google Scholar
D. Magrin, M. Centenaro, and L. Vangelista, “Performance evaluation of LoRa networks in a smart city scenario,” in IEEE International Conference on Communications, 2017. doi: 10.1109/ICC.2017.7996384.MagrinD.CentenaroM.VangelistaL.“Performance evaluation of LoRa networks in a smart city scenario,”inIEEE International Conference on Communications201710.1109/ICC.2017.7996384Open DOISearch in Google Scholar
M. Bor, U. Roedig, T. Voigt, and J. M. Alonso, “Do LoRa low-power wide-area networks scale?,” in MSWiM 2016 - Proceedings of the 19th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems, 2016. doi: 10.1145/2988287.2989163.BorM.RoedigU.VoigtT.AlonsoJ. M.“Do LoRa low-power wide-area networks scale?,”inMSWiM 2016 - Proceedings of the 19th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems201610.1145/2988287.2989163Open DOISearch in Google Scholar
P. Robyns, P. Quax, W. Lamotte, and W. Thenaers, “A multi-channel software decoder for the LoRa modulation scheme,” in IoTBDS 2018 - Proceedings of the 3rd International Conference on Internet of Things, Big Data and Security, 2018. doi: 10.5220/0006668400410051.RobynsP.QuaxP.LamotteW.ThenaersW.“A multi-channel software decoder for the LoRa modulation scheme,”inIoTBDS 2018 - Proceedings of the 3rd International Conference on Internet of Things, Big Data and Security201810.5220/0006668400410051Open DOISearch in Google Scholar
M. Bor, J. Vidler, and U. Roedig, “Lora for the internet of things,” in International Conference on Embedded Wireless Systems and Networks, 2016.BorM.VidlerJ.RoedigU.“Lora for the internet of things,”inInternational Conference on Embedded Wireless Systems and Networks2016Search in Google Scholar
J. Petäjäjärvi, K. Mikhaylov, M. Pettissalo, J. Janhunen, and J. Iinatti, “Performance of a low-power wide-area network based on lora technology: Doppler robustness, scalability, and coverage,” Int J Distrib Sens Netw, vol. 13, no. 3, 2017, doi: 10.1177/1550147717699412.PetäjäjärviJ.MikhaylovK.PettissaloM.JanhunenJ.IinattiJ.“Performance of a low-power wide-area network based on lora technology: Doppler robustness, scalability, and coverage,”Int J Distrib Sens Netw133201710.1177/1550147717699412Open DOISearch in Google Scholar
L. Vangelista, “Frequency Shift Chirp Modulation: The LoRa Modulation,” IEEE Signal Process Lett, vol. 24, no. 12, 2017, doi: 10.1109/LSP.2017.2762960.VangelistaL.“Frequency Shift Chirp Modulation: The LoRa Modulation,”IEEE Signal Process Lett2412201710.1109/LSP.2017.2762960Open DOISearch in Google Scholar
C. H. Liao, G. Zhu, D. Kuwabara, M. Suzuki, and H. Morikawa, “Multi-Hop LoRa Networks Enabled by Concurrent Transmission,” IEEE Access, vol. 5, 2017, doi: 10.1109/ACCESS.2017.2755858.LiaoC. H.ZhuG.KuwabaraD.SuzukiM.MorikawaH.“Multi-Hop LoRa Networks Enabled by Concurrent Transmission,”IEEE Access5201710.1109/ACCESS.2017.2755858Open DOISearch in Google Scholar
M. S. Khan, S. M. Kim, E. H. Lee, and J. Kim, “Genetic Algorithm Based Cooperative Spectrum Sensing Optimization in the Presence of Malicious Users in Cognitive Radio Networks,” in ICTC 2019 - 10th International Conference on ICT Convergence: ICT Convergence Leading the Autonomous Future, 2019. doi: 10.1109/ICTC46691.2019.8939859.KhanM. S.KimS. M.LeeE. H.KimJ.“Genetic Algorithm Based Cooperative Spectrum Sensing Optimization in the Presence of Malicious Users in Cognitive Radio Networks,”inICTC 2019 - 10th International Conference on ICT Convergence: ICT Convergence Leading the Autonomous Future201910.1109/ICTC46691.2019.8939859Open DOISearch in Google Scholar
J. Chen, S. Huang, H. Li, X. Lv, and Y. Cai, “PSO-Based Agent Cooperative Spectrum Sensing in Cognitive Radio Networks,” IEEE Access, vol. 7, 2019, doi: 10.1109/ACCESS.2019.2944227.ChenJ.HuangS.LiH.LvX.CaiY.“PSO-Based Agent Cooperative Spectrum Sensing in Cognitive Radio Networks,”IEEE Access7201910.1109/ACCESS.2019.2944227Open DOISearch in Google Scholar
M. S. Hossain and M. S. Miah, “Machine learning-based malicious user detection for reliable cooperative radio spectrum sensing in Cognitive Radio-Internet of Things,” Machine Learning with Applications, vol. 5, 2021, doi: 10.1016/j.mlwa.2021.100052.HossainM. S.MiahM. S.“Machine learning-based malicious user detection for reliable cooperative radio spectrum sensing in Cognitive Radio-Internet of Things,”Machine Learning with Applications5202110.1016/j.mlwa.2021.100052Open DOISearch in Google Scholar