Abstract
This paper presents robust empirical path loss models to characterize indoor propagation for access point (AP) deployed at different heights. The proposed models are developed with wireless local area network infrastructure at 2.4 GHz. The models are backed by extensive received signal strength (RSS) measurements acquired in line of sight and obstructed line of sight regions. The models are developed for two conditions, viz; quasi realistic and realistic RSS measurements. The quasi realistic measurements are taken after suppressing human intervention and electrical interferences to minimum. While the realistic RSS measurements are made in presence of all the human interventions and electrical interferences. The shadow fading component for both quasi realistic and realistic conditions is statistically modeled with the dependency on AP height. The proposed technique can be applied with higher confidence level to the buildings with similar construction features where RSS measurements are made upon. The results reveal that the performance of the proposed propagation models is significantly higher than the existing International Telecommunication Union-path loss model. The results also demonstrate that the realistic path loss model is more robust than the quasi realistic model.
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References
Prasad, N. R., & Alam, M. (2006). Security frame work for wireless sensor networks. Wireless Personal Communications, 37(3–4), 455–469.
Seybold, J. S. (2005). Introduction to RF propagation. New Jersey: Wiley.
Nerguizian, C., Despins, C. L., Affes, S., & Djadel, M. (2005). Radio channel characterization of an underground mine at 2.4 GHz. IEEE Transactions on Wireless Communications, 4(5), 2441–2453.
Fernandez, O., Domingo, M., & Torres, R. (2004). Experimental analysis of wireless data transmission systems in space platforms. IEEE Transactions on Antennas and Propagation Magazine, 46(4), 38–46.
Chrysikos, T., Gorgophoulos, G., Kotsiopoulos. S., & Zevgolis. D. (2010). Site-specific validation of indoor RF propagation models for commercial propagation topologies at 2.4 GHz. In Proceedings of the ISWCS conference (pp. 681–685).
Zygiridis, T. T., Kosmiden, E. P., Protopidis, K. P., Kantratizis, N. V., Antonopoulos, C. V., Petras, K. I., et al. (2006). Numerical modeling of an indoor wireless environment for the performance evaluation of WLAN Systems. IEEE Transactions on Magnetics, 42(4), 839–842.
Neskovic, A., Neskovic, N., & Paunovic, D. (2000). Modern approaches in modeling of mobile radio systems propagation environment. IEEE communication surveys, Third quarter (pp. 1–12).
Pahlavan, K., & Krishnamurthy, P. (2005). Principles of wireless networks. New Delhi: PHI.
Sarkar, T., Ji, Z., Kim, K., Medouri, A., & Salzar-Palma, M. (2003). A survey of various propagation models for mobile communication. IEEE Antennas and Propagation Magazine, 45(3), 51–82.
Akl, R., Tummala, D., & Li, X. (2006). Indoor propagation modeling at 2.4 GHz for IEEE 802.11 networks. In Proceedings of sixth International multi conference wireless networks and emerging technologies Banff, Canada.
Tarng, J. H., Chang, W. R., & Hsu, B. J. (1997). Three dimensional modeling of 900 MHz and 2.44 GHz radio propagation in corridors. IEEE Transactions on Vehicular Technology, 46(2), 519–527.
Yang, C., Wu, B., & Ko, C. (1998). A ray tracing method for modeling indoor wave propagation and penetration. IEEE Transactions on Antennas and Propagation, 46(6), 907–919.
Rappaport, T. (2002). Wireless communications: Principles and practice. Upper Saddle River: Pearson Education Inc.
ITU-R recommendations ITU-R.P.1238-7 propagation data and propagation methods for the planning of indoor radio communications systems and radio local area networks in the frequency range 900MHz to 100GHz. http://www.itu.int/pub/R-Rec/en. Accessed on February 20, 2013.
Plets, D., Joseph, W., Verloock, L., Tanghe, E., & Marten, L. (2010). Evaluation of indoor penetration loss and floor loss for DVB-H signal at 514 MHz. In Proceedings of IEEE international symposium on broad band multimedia systems and broad casting (pp 1–6). Shangai.
Joseph, W., Verloock, L., Plets, D., Tanghe, E., & Martens, L. (2009). Characterization of coverage and indoor penetration loss of DVB-H signal of indoor gap filler in UHF band. IEEE Transactions on Broad Casting, 55(3), 589–597.
Todd, S., Tanany, E., Kalivas, G., & Mahmoud S. (1993). Indoor radio path loss comparison between the 1.7GHz and 37 GHz bands. In Proceedings of second international conference on universal personal communications, Gateway to the 21st century (Vol. 2, pp. 621–625).
Cerpulli, F., Monti, C., Vari, M., & Mazzevga, I. (2006). Path loss models for IEEE 802.11a wireless local area networks. In Proceedings of 3rd international conference on wireless communication systems, ISWCS 06 (pp. 621–624). Valencia, Spain.
Nazallaer, A., Park, Y., Yoo, K., & Yu, J. (2011). A fast and accurate calibration algorithm for real time locating systems based on the received signal strength indication. International Journal of Electronics and Communications AEU, 65, 305–311.
Chrysikos, T., Georgopoulus, G., & Kotsopoulos, S. (2009). Site specific validation of ITU indoor path loss model at 2.4 GHz. In Proceedings of WOWMOM conference (pp. 1–6).
Chrysikos, T., Georgopoulus, G., & Kotsopolous, S. (2011). Wireless channel characterization for a home indoor propagation topology at 2.4 GHz. In Proceedings of Wireless telecommunication symposium (WTS) (pp. 1–10).
Ata, O. W., Shahateet, A. M., Jawadeh, M. M., & Amro, A. I. (2013). An indoor propagation model based on a novel multiwall attenuation loss formula at frequencies 900 MHz and 2.4 GHz. Wireless Personal Communications, 69, 23–36.
Dobkin, D. (2002). Indoor propagation issues for wireless LANs, RF design Magazine, Sept., pp. 40–46.
Anderson, J. B., Rappaport, T. S., & Yoshida, S. (1995). Propagation measurements and models for wireless communication channels. IEEE Communications Magazine, 33(1) 42–49.
Cheung, K., Sau, J. H. M., & Murch, R. D. (1998). A new empirical model for indoor propagation prediction. IEEE Transactions on Vehicular Technology, 47(3), 996–1001.
Prasad, A. R., Prasad, N. R., Kamerman, A., Moelard, H., & Eikelenboom, A. (2001). Performance evaluation system design and network deployment of IEEE 802.11. Wireless Personal Communications, 19, 57–79.
Milner, M. (2004). Netstumbler 0.4.0 notes available on line: http://www.stumbler.net/readme/readme_0_4_0.html.pdf. Accessed on February 20, 2013
Bahl, P., & Padmanabhan, V. (2000). RADAR: An in building RF based user location and tracking system. In Proceedings of the 19th IEEE InfoCom conference (Vol. 2, pp. 775–784).
Ladd, A. M., Bekris, K. E., Rudys, A., Kavaraki, L. E., & Wallach, D. S. (2004). On feasibility of using wireless ethernet for indoor localization. IEEE Transactions on Robot Automation, 20(3), 555–559.
Murkami, T., Matsumoto, Y., Fujii, K., Sugiura, A., & Yamanaka, Y. 2003. Propagation Characteristics of the microwave oven noise interfering with wireless systems in the 2.4 GHz band. In The proceedings of 14th IEEE symposium personal, indoor and mobile radio communications (pp. 2726–2729).
Jo, J., & Jayant, N. (2003). Performance evaluation of multiple IEEE 802.11b WLAN stations in the presence of Bluetooth radio interference. In Proceedings of IEEE international conference on communications 2003 (pp. 1163–1168).
Zhang, R., Guo, J., Chu, F., & ChangZhang, Y. (2011). Environmental adaptive indoor radio path loss model for wireless sensor networks localization. International Journal of Electronics and Communications (AEU), 65, 1023–1031.
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Naik, U., Bapat, V.N. Adaptive Empirical Path Loss Prediction Models for Indoor WLAN. Wireless Pers Commun 79, 1003–1016 (2014). https://doi.org/10.1007/s11277-014-1914-9
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DOI: https://doi.org/10.1007/s11277-014-1914-9