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Öğe An analytical and simulation model for IEEE 802.11af based cognitive radio sensor networks(Gazi Univ, Fac Engineering Architecture, 2025) Demirturk, Burak; Bayrakdar, Muhammed EnesIn this study, a cognitive radio sensor network based on IEEE 802.11af technology is proposed for data with priority classes. In IEEE 802.11af technology, the White Space Device (WSD), Station (STA), and Access Point (AP) communicate opportunistically over the television white spectrum without causing any harmful interference to licensed services. In the proposed network structure; WSDs, STA and AP use the Frequency Division Multiple Access (FDMA) technique to communicate over the white space spectrum determined by the White Space Map (WSM). WSD collects data such as temperature, humidity, pressure from sensors in various environments. The priority class is determined as red, yellow and green depending on the urgency of the data. After the analytical model of the proposed network was obtained, the simulation model was implemented using Riverbed Modeler. The graphical results prove the validity and feasibility of the proposed network in terms of latency (0.17 s) and energy consumption (4.7 mJ/s) without any spectrum cost for monitoring priority-based data.Öğe Cognitive Sensor Network-Based Emergency Notification in Smart Agriculture(Ieee-Inst Electrical Electronics Engineers Inc, 2025) Demirturk, Burak; Bayrakdar, Muhammed EnesIn this study, a cognitive radio sensor network based on IEEE 802.11af technology is proposed for agricultural data with priority classes in smart agriculture. In IEEE 802.11af technology, the white space device (WSD), station (STA), and access point (AP) communicate over the television white spectrum without causing any harmful interference to primary services. In the proposed network structure, WSDs, STA, and AP use the frequency division multiple access (FDMA) technique to communicate over the white space spectrum determined by the white space map (WSM). WSD collects data, such as temperature, humidity, and pressure, from sensors in agricultural areas. The priority class is determined as red, yellow, and green. Depending on the emergency of the agricultural data, the aging solution is adopted for starvation mitigation in the queue. After the analytical model of the proposed network was obtained, the simulation model was implemented using Riverbed Modeler. The graphical results prove the validity and feasibility of the proposed network without any spectrum cost for monitoring priority-based agricultural data.












