Wavelet Based Residual Method of Detecting GSM Signal Strength Fading

In this paper, GSM signal strength was measured in
order to detect the type of the signal fading phenomenon using onedimensional
multilevel wavelet residual method and neural network
clustering to determine the average GSM signal strength received in
the study area. The wavelet residual method predicted that the GSM
signal experienced slow fading and attenuated with MSE of 3.875dB.
The neural network clustering revealed that mostly -75dB, -85dB and
-95dB were received. This means that the signal strength received in
the study is a weak signal.





References:
[1] Sami A. Mawjoud "Path Loss Propagation Model Prediction for GSM network planning”, International Journal of Computer Applications, Vol. 84, No. 7, December, 2013.
[2] European Cooperation in the Field of Scientific and Technical Research Euro- Cost 231 urban Transmission loss Model for Mobile Radio in the 900 MHz and 1800MHz Bands. Revision2, TheHague, September, 1991
[3] Goldsmith A., "Wireless Communication", USA, Cambridge University Press, 2005
[4] J. Wu and D. Yuan, "Propagation Measurements and Modeling in Jinan City”, IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, Boston, MA, USA, Vol. 3, pp. 1157- 1159, 8-11 September 1998
[5] Z. Nadir, I. Aeng, N. Flfadhil, and F. Touati," Path Loss Determination Using Okumura-Hata Model and spline Interpolation for Missing Data for Oman", Proceedings of the World Congress on Engineering, Vol. 1,pp. 2-4,UK,July, 2008
[6] M., "Empirical Formula For Propagation Loss in Land Mobile Radio Services", IEEE Transaction on Vehicular Technology Vol. 29,No. 3, 1980.
[7] Y. Okumura et al., Field Strength and Its Variability In VHF and UHF Land-Mobile Radio Service, Review of the Electrical Communications Laboratory, Vol. 16, no. 9-10, September-October,1968
[8] V. Erceg, L. Greenstein, "An Empirical Based Path Loss Model for Wireless Channels in Suburban Environments", IEEE Journal on Selected Areas of Communication, Vol. 17, pp/ 1205-1211, July, 1999
[9] S. R. Saunders M. Hata, "Empirical Formula for Propagation Loss in Land Mobile Radio Services”, IEEE Transactions on Vehicular Technology, Vol. VT 29. August 1980.
[10] A. Medeisis and A. Kajackas, "On the Use of the Universal Okumura-Hata Propagation Predication Model in Rural Areas”, Vehicular Technology Conference Proceedings of VTC, Tokyo, Vol.3 pp.1815-1818, May, 2000.
[11] Xiaobo Long and BiplabSikdar. Wavelet Based Detection of Shadow Fading in Wireless Networks. Electrical, Computer and System Engineering Rensselaer Polytechnic Institute, 110 8th Street, Troy NY 12180.
[12] Yuvraj Singh, "Comparison of Okumura, Hata and COST-231 on the bases of the path loss and signal strength” International Journal of Computer and Application, Vol. 59 No. 11, December, 2012
[13] Danladi Ali and Vlada N.Y. Wavelet based path loss modeling for global system for mobile communication in an urban environment International Journal of Science and Research 3(7): 1929-1932
[14] Danladi Ali and V.V. Gnatushenko” Estimation of Hurst Exponent and Filtering of Gaussian effect on Fractional Brownian Motion” Proc. of the Intl. Conf. on Advances In Computing, Communication and Information Technology. Institute of Research Engineers and Doctors, pp. 40-44. ISBN: 978-1-63248-010-1 doi: 10.15224/ 978-1-63248-010-1-08