Fadeyi, JMarkus, EDAbu-Mahfouz, Adnan MI2019-10-282019-10-282019-06Fadeyi, J., Markus, E.D. & Abu-Mahfouz, A.M.I. 2019. Technology coexistence in LPWANs-A comparative analysis for spectrum optimization. In: 2019 IEEE 28th International Symposium on Industrial Electronics (ISIE), Vancouver, Canada, 12-14 June 2019978-1-7281-3666-0978-1-7281-3667-7https://ieeexplore.ieee.org/document/8781310DOI: 10.1109/ISIE.2019.8781310http://hdl.handle.net/10204/11191Copyright: 2019 IEEE. Due to copyright restrictions, the attached PDF file only contains the abstract of the full text item. For access to the full text item, please consult the publisher's website.Low-Power Wide-Area Networks (LPWANs) are designed to overcome range and scalability problems encountered by traditional cellular networks and short-range communication technologies. This has brought a revolution to wireless communications in an unprecedented manner. Internet of things (IoT) on the other hand allows the connectivity of these networks to take place. The most suitable technology for many IoT applications is the LPWAN due to some characteristics peculiar to this technology like low power, long battery life, wide coverage and low deployment and operational costs. Many of LPWAN technologies are found in the unlicensed spectrum with a lot of different technologies deployed at close range, congestion and interference are bound to occur. Hence, the spectrum needs to be optimized for efficiency, reliability and better quality of service. This paper reviews different optimization techniques in an environment of technology coexistence, the merits and demerits of the different techniques and its application to LPWANs. The paper also highlights the recommendations and future directions for spectrum optimization in LPWANs.enCongestionInternet of ThingsInterferenceOptimizationTechnology CoexistenceTechnology coexistence in LPWANs-A comparative analysis for spectrum optimizationConference PresentationFadeyi, J., Markus, E., & Abu-Mahfouz, A. M. (2019). Technology coexistence in LPWANs-A comparative analysis for spectrum optimization. IEEE. http://hdl.handle.net/10204/11191Fadeyi, J, ED Markus, and Adnan MI Abu-Mahfouz. "Technology coexistence in LPWANs-A comparative analysis for spectrum optimization." (2019): http://hdl.handle.net/10204/11191Fadeyi J, Markus E, Abu-Mahfouz AM, Technology coexistence in LPWANs-A comparative analysis for spectrum optimization; IEEE; 2019. http://hdl.handle.net/10204/11191 .TY - Conference Presentation AU - Fadeyi, J AU - Markus, ED AU - Abu-Mahfouz, Adnan MI AB - Low-Power Wide-Area Networks (LPWANs) are designed to overcome range and scalability problems encountered by traditional cellular networks and short-range communication technologies. This has brought a revolution to wireless communications in an unprecedented manner. Internet of things (IoT) on the other hand allows the connectivity of these networks to take place. The most suitable technology for many IoT applications is the LPWAN due to some characteristics peculiar to this technology like low power, long battery life, wide coverage and low deployment and operational costs. Many of LPWAN technologies are found in the unlicensed spectrum with a lot of different technologies deployed at close range, congestion and interference are bound to occur. Hence, the spectrum needs to be optimized for efficiency, reliability and better quality of service. This paper reviews different optimization techniques in an environment of technology coexistence, the merits and demerits of the different techniques and its application to LPWANs. The paper also highlights the recommendations and future directions for spectrum optimization in LPWANs. DA - 2019-06 DB - ResearchSpace DP - CSIR KW - Congestion KW - Internet of Things KW - Interference KW - Optimization KW - Technology Coexistence LK - https://researchspace.csir.co.za PY - 2019 SM - 978-1-7281-3666-0 SM - 978-1-7281-3667-7 T1 - Technology coexistence in LPWANs-A comparative analysis for spectrum optimization TI - Technology coexistence in LPWANs-A comparative analysis for spectrum optimization UR - http://hdl.handle.net/10204/11191 ER -