LNG ORTAMINDA ÇALIŞAN TELSİZ DUYARGA AĞLARI İÇİN GİGAHERTZ KANAL MODELLENMESİ

Yıl 2017, Cilt: 22 Sayı: 2, 75 - 84, 29.08.2017

Mustafa Alper Akkaş

https://doi.org/10.17482/uumfd.336405

Öz

LNG (Sıvılaştırılmış Doğal Gaz) doğal gazın -162
ºC’de soğutulması ile oluşturulan temiz, renksiz ve zehirsiz bir sıvıdır. Bu
soğutma işlemi sayesinde doğal gazın hacmi 600 kat daha küçültülerek, LNG’nin
depolanmasını ve taşınmasını kolaylaştırmaktadır. LNG' nin özgül ağırlığı
basınç, sıcaklık ve karışıma göre değişir ve ortalama 1,0 kg/litre su ile
mukayese edildiğinde, 0,46 kg/litre’ye eşittir. LNG’nin özgül ağırlığının düşük
olması elektromanyetik dalgaların yayılımı ve TDA (Telsiz Duyarga Ağları)’nın
haberleşebilmesi için bir avantajdır. Ayrıca bu çalışmada TDA’lar için LNG yol
kaybı, yansıma etkisi ve BHO (Bit Hata Oranı)’a ya göre LNG ortamı analiz
edilip, modellenmiştir. Yayılım karakteristikleri teorik yaklaşım ile
incelenmiştir. Teorik analizler ve simülasyon sonuçları 10 GHz – 13 GHz bant
aralığında, 10 metre civarı bir kablosuz haberleşme olacağını ispatlamaktadır.

Anahtar Kelimeler

LNG, Telsiz Duyarga Ağları, Elektromanyetik Modelleme

Gigahertz Channel Modeling for Wireless Sensor Networks Operating in LNG Environment

Öz

LNG (Liquefied Natural Gas)
is a clear, colorless and non-toxic liquid which forms when natural gas is
cooled to -162 ºC. The cooling process shrinks the volume of the gas 600 times,
by this way making LNG easier and safer to store and ship. The density of LNG
is around 0.46 kg/liter, depending on pressure, temperature, and
composition, compared to water at 1.0 kg/liter. The lesser density of LNG
is also an advantage for the propagation of the electromagnetic waves and
communication of WSN (Wireless Sensor Networks) in LNG medium. Then here in
this work LNG has analyzed according to path loss, multipath effect and
providing an evaluation about the Bit Error Rate (BER) of the modelled channel
depending on the LNG medium for WSNs. The propagation characteristics are
investigated using a theoretical approach. The theoretical analysis and the
simulation results prove the feasibility of wireless communication about 10 m
range in the 10 GHz – 13 GHz band range in LNG medium.

Anahtar Kelimeler

LNG, Wireless Sensor Networks, Electromagnetic Modelling

Kaynakça

• Akkaş, M. A. ve Sokullu, R. (2015). Channel modeling and analysis for wireless underground sensor networks in water medium using electromagnetic waves in the 300–700 MHz range. Wireless Personal Communications, 84(2), 1449-1468.
• Akkaş, M. A., Akyildiz, I. F. ve Sokullu, R. (2012, December). Terahertz channel modeling of underground sensor networks in oil reservoirs. In Global Communications Conference (GLOBECOM), 2012 IEEE (pp. 543-548). IEEE. doi: 10.1109/GLOCOM.2012.6503169.
• Akyildiz, I. F., & Jornet, J. M. (2010). Electromagnetic wireless nanosensor networks. Nano Communication Networks, 1(1), 3-19. doi: 10.1016/j.nancom.2010.04.001.
• Akyildiz, I. F., Sun, Z. ve Vuran, M. C. (2009). Signal propagation techniques for wireless underground communication networks. Physical Communication, 2(3), 167-183. doi: 10.1016/j.phycom.2009.03.004.
• Cheng, D. K. (1989). Field and wave electromagnetics. Pearson Education India.
• Elrashidi, A., Elleithy, A., Albogame, M. ve Elleithy, K. (2012, March). Underwater wireless sensor network communication using electromagnetic waves at resonance frequency 2.4 GHz. In Proceedings of the 15th Communications and Networking Simulation Symposium (p. 13). Society for Computer Simulation International.
• Gutierrez, G. ve Vincent, J. L. (Eds.). (2012). Tissue oxygen utilization (Vol. 12). Springer Science & Business Media. doi: 10.1007/978-3-642-84169-9.
• Jornet, J. M. ve Akyildiz, I. F. (2013). Fundamentals of electromagnetic nanonetworks in the terahertz band. Foundations and Trends® in Networking, 7(2-3), 77-233. doi: 10.1561/1300000045.
• Li, L., Vuran, M. C. ve Akyildiz, I. F. (2007). Characteristics of underground channel for wireless underground sensor networks. Proc. Med-Hoc-Net’07.
• Mao, G., Anderson, B. D. ve Fidan, B. (2007). Path loss exponent estimation for wireless sensor network localization. Computer Networks, 51(10), 2467-2483. doi: 10.1016/j.comnet.2006.11.007.
• Paillou, P., Mitchell, K., Wall, S., Ruffié, G., Wood, C., Lorenz, R., ... & Encrenaz, P. (2008). Microwave dielectric constant of liquid hydrocarbons: Application to the depth estimation of Titan's lakes. Geophysical Research Letters, 35(5). doi: 10.1029/2007GL032515.
• Remeljej, C. W. ve Hoadley, A. F. A. (2006). An exergy analysis of small-scale liquefied natural gas (LNG) liquefaction processes. Energy, 31(12), 2005-2019. doi: 10.1016/j.energy.2005.09.005.
• Silva, A. R. (2010). Channel characterization for wireless underground sensor networks.
• Silva, A. R. ve Vuran, M. C. (2009, June). Empirical evaluation of wireless underground-to-underground communication in wireless underground sensor networks. In International Conference on Distributed Computing in Sensor Systems (pp. 231-244). Springer Berlin Heidelberg. doi: 10.1007/978-3-642-02085-8_17.
• Vuran, M. C. ve Akyildiz, I. F. (2008, April). Cross-layer packet size optimization for wireless terrestrial, underwater, and underground sensor networks. In INFOCOM 2008. The 27th Conference on Computer Communications. IEEE (pp. 226-230). IEEE. doi: 10.1109/INFOCOM.2008.54.
• Vuran, M. C. ve Akyildiz, I. F. (2010). Channel model and analysis for wireless underground sensor networks in soil medium. Physical Communication, 3(4), 245-254. doi: 10.1016/j.phycom.2010.07.001.
• Zednik, J. J., Dunlavy, D. L. ve Scott, T. G. (2000). U.S. Patent No. 6,089,022. Washington, DC: U.S. Patent and Trademark Office.