An analytical and simulation model for IEEE 802.11af based cognitive radio sensor networks

Yıl 2025, Cilt: 40 Sayı: 3, 1823 - 1836, 21.08.2025

Burak Demirtürk Muhammed Enes Bayrakdar

https://doi.org/10.17341/gazimmfd.1466774

Öz

In 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.

Anahtar Kelimeler

Cognitive Radio , IEEE 802.11af , Priority , Wireless Sensor Networks

IEEE 802.11af tabanlı bilişsel radyo algılayıcı ağlar için bir analitik ve benzetim modeli uygulaması

Öz

Bu çalışmada, öncelik sınıflarına sahip veriler için IEEE 802.11af teknolojisi tabanlı bilişsel radyo algılayıcı ağ önerilmektedir. IEEE 802.11af teknolojisinde Beyaz Uzay Cihazı (WSD), İstasyon (STA) ve Erişim Noktası (AP), lisanslı hizmetlere herhangi bir zararlı müdahaleye neden olmadan, televizyon beyaz spektrumu üzerinden fırsatçı bir şekilde iletişim kurar. Önerilen ağ yapısında; WSD'ler, STA ve AP, Beyaz Uzay Haritası (WSM) tarafından belirlenen beyaz alan spektrumu üzerinden iletişim kurmak amacıyla Frekans Bölmeli Çoklu Erişim (FDMA) tekniğini kullanır. WSD, çeşitli ortamlardaki sensörlerden sıcaklık, nem, basınç gibi verileri toplar. Öncelik sınıfı verinin aciliyet durumuna göre kırmızı, sarı ve yeşil olarak belirlenmiştir. Önerilen ağın analitik modeli elde edildikten sonra Riverbed Modeler kullanılarak benzetim modeli gerçekleştirilmiştir. Grafiksel sonuçlar, öncelik bazlı verilerin izlenmesi için herhangi bir spektrum maliyeti olmadan, önerilen ağın gecikme (0,17 s) ve enerji tüketimi (4,7 mJ/s) açısından geçerliliğini ve uygulanabilirliğini kanıtlamaktadır.

Anahtar Kelimeler

Bilişsel Radyo , IEEE 802.11af , Öncelik , Kablosuz Algılayıcı Ağlar

Kaynakça

• 1. Panbude S., Iyer B., Nandgaonkar A. B., Deshpande P. S., DFPC: Dynamic Fuzzy-based Primary User Aware clustering for Cognitive Radio Wireless Sensor Networks, Eng. Technol. Appl. Sci. Res., 13 (6), 12058-12067, 2023.
• 2. Wang J., Liu C., An imperfect spectrum sensing-based multi-hop clustering routing protocol for cognitive radio sensor networks. Sci Rep, 13, 4853, 2023.
• 3. Wang J., Wang Z., Zhang L. A., Simultaneous Wireless Information and Power Transfer-Based Multi-Hop Uneven Clustering Routing Protocol for EH-Cognitive Radio Sensor Networks, Big Data Cogn. Comput., 8 (2), 15, 2024.
• 4. Singh S., Shrestha R., A New Hardware-Efficient and Low Sensing-Time Cooperative Spectrum-Sensor for High-Throughput Cognitive-Radio Network, IEEE Trans. Circuits Syst. I Regul. Pap., 71 (1), 262-273, 2024.
• 5. Bala V. J., Saswat K. R., Deepan, Energy-efficient adaptive sensing for Cognitive Radio Sensor Network in the presence of Primary User Emulation Attack, Comput. Electr. Eng., 106, 2023.
• 6. Lu L., Xu W., Wang Y., Compressive Spectrum Sensing Using Blind-Block Orthogonal Least Squares in Cognitive Sensor Networks, IEEE Sens. J., 23 (24), 30573-30583, 2023.
• 7. Kumar D., Singya P. K., Choi K., Bhatia V., SWIPT Enabled Cooperative Cognitive Radio Sensor Network With Non-Linear Power Amplifier, IEEE Trans. Cognit. Commun. Networking, 9 (4), 884-896, 2023.
• 8. Raghavendra Y. M., Mahadevaswamy U. B., Asha, M., Energy Optimization in Spectrum Sensing Using Cognitive Radio Wireless Sensor Networks, Wireless Pers Commun, 133, 1675-1691, 2023.
• 9. Zhang B., An Efficient Cooperative Spectrum Sensing for Cognitive Wireless Sensor Networks, IEEE Access, 11, 132544-132556, 2023.
• 10. Babu R. G., Hemanand D., Amudha V., Sugumaran S., Design of clustering techniques in cognitive radio sensor networks, Comput. Syst. Sci. Eng., 44 (1), 441-456, 2023.
• 11. Flores A. B., Guerra R. E., Knightly E. W., Ecclesine P., Pandey S., IEEE 802.11af: a standard for TV white space spectrum sharing, IEEE Commun. Mag., 51 (10), 92-100, 2013.
• 12. Cheang C., Un K., Yu W., Mak P., Martins R. P., A Combinatorial Impairment-Compensation Digital Predistorter for a Sub-GHz IEEE 802.11af-WLAN CMOS Transmitter Covering a 10x-Wide RF Bandwidth, IEEE Trans. Circuits Syst. I Regul. Pap., 62 (4), 1025-1032, 2015.
• 13. Un K., Yu W., Cheang C., Qi G., Mak P., Martins R. P., A Sub-GHz Wireless Transmitter Utilizing a Multi-Class-Linearized PA and Time-Domain Wideband-Auto I/Q-LOFT Calibration for IEEE 802.11af WLAN, IEEE Trans. Microwave Theory Tech., 63 (10), 3228-3241, 2015.
• 14. Matsumura T., Ibuka K., Ishizu K., Murakami H., Kojima F., Harada H., Prototype of IEEE 802.11af-Based Baseband IC Enabling Compact Device for Wireless Local Area Network Systems in TV White-Spaces, IEEE Trans. Cognit. Commun. Networking, 3 (3), 450-463, 2017.
• 15. Basgumus A., Namdar M., Tsiftsis T., Broadcast Cognitive Radio with Dirty Paper Coding over Nakagami-m Fading Channel, Advances in Electrical and Computer Engineering, 191, 3-8, 2019.
• 16. Erdogan E, Çolak SA, Alakoca H, Namdar M, Basgumus A, Durak-Ata L. Interference Alignment in Multi-Hop Cognitive Radio Networks under Interference Leakage. Applied Sciences, 8 (12), 2486, 2018.
• 17. Başgümüş A., Ardıç M.S., Namdar M., Capacity analysis of the secondary users in spectrum sharing model over Nakagami- m and log-normal fading channels, Journal of the Faculty of Engineering and Architecture of Gazi University, 38 (4), 2205-2212, 2023.
• 18. IEEE 802.11af, Standart, https://standards.ieee.org/ieee/802.11af/4761/, Yayın Tarihi Şubat, 2014, Erişim Tarihi Mart, 2024.
• 19. Riverbed Modeler, Benzetim Yazılımı, https://www.riverbed.com/, Yayın Tarihi Aralık, 2022, Erişim Tarihi Mart, 2024.