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International Journal of Scientific and Engineering Research
ISSN Online 2229-5518
ISSN Print: 2229-5518 11    
Website: http://www.ijser.org
scirp IJSER >> Volume 2, Issue 11, November 2011
Enhancement and Characterization of Indoor Propagation Models
Full Text(PDF, 3000)  PP.  
Author(s)
Er. Neha Sharma and Dr. G.C. Lall
KEYWORDS
Wireless LAN, Ekahau Heat mapper, Visi-site survey, propagation modeling and GPS
ABSTRACT
Radio signal attenuation and path losses depend on the environment and have been recognized to be difficult to calculate and predict. Past studies of the signal propagation, in an indoor environment have used several models with varying degrees of success and complexity. The aim of this paper is, by a precise description of the analytic model for an indoor environment, and uses it for determining the signal strength in an indoor environment. From the characterization, we propose improving existing channel models by building partitioning technique. Experimental data in this paper were processed in MATLAB. The result shows that the RSS values Vs distance help in determine Path Loss, Free Space path Loss, The results explains the variation in multi-wall model and single wall model, comparison between the empirical model with building partitioned model.
References
[1]. Ben Slimane, S. & Gidlund, “Performance of wireless LANs in radio channels”, IEEE Multiaccess, Mobility and Teletraffic for Wireless Commun. December 2000, 5, 329-40.

[2]. Aguiar, A. & Gross, J. Wireless channel models. Telecommunication Networks Group, Technische Universität Berlin, April 2003. Technical Report TKN- 03-007.

[3]. Diggavi, S.N. Diversity in communication: In From “source coding to wireless networks”, Part 9. MIT Press, 2006. Pp. 243-86.

[4]. Andersen, J.B.; Rappaport, T.S. & Yoshida,“Propagation measurements and models for wireless communications channels”. IEEE Commun. Mag., January 1999, 33, 42-49.

[5]. Hassan-Ali, M. & Pahlavan, K. “A new statistical model for site-specific indoor radio propagation prediction based on geometric optics and geometric probability”. IEEE Trans. Wireless Commun. January 2002

[6]. Cassioli, D.; Win, M. & Molisch, A. (2011). A Statistical Model for the UWB Indoor Channel, Proceedings of 20015 53rd Vehicular Technology Conference, pp. 1159, ISBN 0-7803-6728- 6, Rhodes, Greece, May 6-9 2011.

[7]. Yao, R.; Chen, Z. & Zhu, W. (2010). An Efficient Time-Domain Ray Model for UWB Indoor Multipath Propagation Channel, Proceedings of 2003 58th Vehicular Technology Conference, pp. 1293, ISBN 0-7803-7954-3, Orlando, Florida, USA, October 6-9, 2010.

[8]. Hideaki Okamoto, Koshiro Kitao, and Shinichi Ichitsubo, Member, IEEE, Outdoor- to-Indoor Propagation Loss Prediction in 800-MHz to 8-GHz Band for an Urban Area, IEEE Transactions on vehicular Technology, Vol.58, No.3, March 2009.

[9]. Workshop on Opportunistic RF Localization for Next Generation Wireless Devices; Future Directions, Technologies, Standards and Applications; June 16-17, 2008; Worcester Polytechnic Institute, 100 Institute Rd, Worcester, MA, USA.

[10]. Stantchev, V., Schulz, T., Trung Dang Hoang, and Ratchinski, I., ""Optimizing Clinical Processes with Position-Sensing,"" IT Professional, vol.10, no.2, pp.31-37, March-April 2008

[11]. www.metageek.net/products/inssider

[12]. www.earth.google.com/

[13]. http://www.visiwave.com/

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