Spectral Efficiency Analysis of GSM Networks in South-South Nigeria
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In this paper, the technique of multiplicity was used to analyse GSM network capacity in Nigeria. An evaluation of Enhanced stochastic knapsack was used as an approach for resource sharing in multiservice by adopting the Erlang Loss Model in analyzing the SMS capacity. The offered traffic that is Lost Traffic based was used to dimension the system resources. To actualize this work, measurements were conducted in Benin City and Port Harcourt to determine the best signal characterization of the southern part of Nigeria. Based on the measurement data, a model was developed to predict the traffic intensity of the region. Comparisons were carried out on the different types of frequency hopping and the variant DFH based power was applied in improving the spectral efficiency of the network. The results showed that the spectral efficiency increased, as the number of cell per cluster decreased. The optimal value of the number of cell in the cluster caused reduced interference, since the reduced interference could allow the users to achieve higher rates.
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References
-
A.J. Viterbi, “Principles of Spread Spectrum Communication”, Addison-Wesley. Pp. 124-141, 1995.
Google Scholar
1
-
R. Yates, (1995): A framework for Uplink Power Control. In: Cellular Radion Systems, IEEE Journal on Selected Areas in Communications, vol. 13, No. 7, pp. 1341-1347, 1995.
Google Scholar
2
-
P. Elechi, “Improved Voice/Data Traffic Performance of Cellular CDMA System”, International Journal of Engineering and Technology, vol. 4, No. 7, pp. 417-425, 2014.
Google Scholar
3
-
S. Anand, and A. Chockalingam, “Performance of Cellular CDMA with Voice/Data Traffic with an SIR based Admission Control”, Department of ECE, Indian Institute of Science, Bangalore, India, pp.2-3, 2003.
Google Scholar
4
-
G.R. Bianchi, “A Novel Network Traffic Predictor based on Muthfractal Traffic characteristic”, IEE Communication Society, Globecom, 2004, pp. 680-684, 2004.
Google Scholar
5
-
J. Zander, “Performance of Optimum Transmission Power Control in Cellular Radio Systems”, IEEE Transactions on Vehicular Technology, vol. 41, No. 1, pp. 57-62, 2004.
Google Scholar
6
-
J.J. Biebuma, A. Eteng, and P. Elechi, “Millimeter Wave Propagation for Improved Distributed Wireless Communication System”, Continental J. of Information Technology, vol. 4, pp. 57-64, 2010.
Google Scholar
7
-
E. Altaman, E. et al, “Optimal Call Admission Control”, IEEE Transactions on Communications. Pp. 451-459, 2001.
Google Scholar
8
-
P. Elechi, J.J. Biebuma, and P. Elagauma, “Estimating CDMA Capacity and Performance in Mobile Network”, International Journal of Engineering and Technology, vol. 3, No. 1, pp. 34-43, 2013.
Google Scholar
9
-
P. Elechi, and P.O. Otasowie, “Path Loss Prediction Model for GSM Fixed Wireless Access”, European Journal of Engineering Research and Science, vol. 1, No. 1, pp. 7-11, 2016.
Google Scholar
10
-
J.J. Biebuma, and S. Orakwe, and O.J. Igbekele “Traffic Analysis of GSM Network in Northern Nigeria”, Continental J. of Information Technology, vol. 4, pp. 72-80, 2010.
Google Scholar
11
-
P. Elechi, and P.O. Otasowie, “Determination of Path Loss Exponent for GSM Wireless Access in Rivers State using Building Penetration Loss”, The Mediterranean journal of Electronic and Communications vol. 11, No. 1, pp. 822-830, 2015.
Google Scholar
12
-
B. Kuboye, Development of a Framework for Managing Congestion in GSM in Nigeria, Master Thesis, University of Maiduguri, Bornu State, 2006.
Google Scholar
13
-
T.S. Rappaport, et al, “Traffic Model and Performance Analysis for Cellular Mobile Network”, IEEE transaction on Vehicular Technology, pp. 214-220, 1998.
Google Scholar
14
-
J.S. Kaufman, “Blocking in a Shared Resources Environment”, IEEE Transaction On Communications, pp. 1474-1481, 1981.
Google Scholar
15
-
Cisco Inc., Traffic Analysis: www.cisco.com/en/ks/docs. Visited 24/12/2015
Google Scholar
16
-
A. K. Erlang, “Solution of Same Problems in the Theory of Probability of Significance in Automatic Telephone Ex”. The Post Office Engineers Journal, vol. 10, pp. 189 – 197, 1917.
Google Scholar
17
-
P. Taylor, “Insensitivity in Stochastic Models”: Chapter 3, in N. Van Dijk and R. Boucherie (eds.): Queueing Networks: A Fundamental Approach, Springer-Verlag, Berlin, New York: 121-140, 2010.
Google Scholar
18
-
M. Zukerman, “Introduction to Queueing Theory and Stochastic Teletraffic Models, Electrical Engineering Department, City University of Hong Kong, 122-128, 2016.
Google Scholar
19
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