On the Statistical Distribution of Packets Service Time in Cellular Access Networks

A. Y. Al-Zahrani


A cellular communication system is divided into two main parts, core network, and radio access network. This research is concerned with the radio access network part which consists of multiple-cells, each served by a central located base station. Furthermore, the users in each cell are considered to be uniformly distributed inside the cell. In the downlink context, the users’ packets usually arrive at the base station via fiber optic and then are relayed to the users via radio waves of certain frequency/ies. The speeds of delivering users’ packets vary, depending on the users’ location. In this paper, the actual distribution of the service time over different users whose locations are uniformly distributed in a cell served by one base station is analytically found. Simulation results are presented to validate the derived model.


wireless network; cumulative distribution function; probability density function; packet service time; resource allocations

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T. S. Rappaport, Wireless communication: principles and practice, Prentice Hall, second edition, 2002

A. Goldsmith, Wireless Communication, Cambridge University Press, first edition, 2005

D. P. Bertsekas, R. G. Gallager, Data networks, Prentice-Hall, 1992

K. Son, H. Kim, Y. Yi, B. Krishnamachari, “Base station operation and user association mechanisms for energy-delay tradeoffs in green cellular networks”, IEEE Journal on Selected Areas in Communications, Vol. 29, pp. 1525-1536, 2011

H. Kim, G. de Veciana, X. Yang, M. Venkatachalam, “α-optimal user association and cell load balancingin wireless networks”, IEEE/ACM Transactions on Networking, Vol. 20, No. 1, pp. 177-190, 2002

D. Niyato, E. Hossain, “Adaptive fair subcarrier/rate allocation in multi rate ofdma networks: radio link level queuing performance analysis”, IEEE Transactions on Vehicular Technology, Vol. 55, No. 6, pp. 1897–1907, 2006

A. Y. Al-Zahrani, “Modelling and qos-achieving solution in full-duplex cellular systems”, International Journal of Computer Networks & Communications, Vol. 10, pp. 117–135, 2018

S. Buyukcorak, G. K. Kurt, O. Cengaver, “A probabilistic framework for estimating call holding time distributions”, IEEE Transactions on Vehicular Technology, Vol. 63, No. 2, pp. 811–821, 2014

A. Leon-Garcia, Probability and random processes for electrical engineering, Addison-Wesley, 1994

M. Azhar, A. Shabbir, “5G networks: challenges and techniques for energy efficiency”, Engineering, Technology & Applied Science Research, Vol. 8, No. 2, pp. 2864-2868, 2018

L. Scalia, K. K. T. Biermann, C. Choi, W. Kellerer, “Power-efficient mobile backhaul design for CoMP support in future wireless access systems”, 2011 IEEE Conference on Computer Communications Workshops, Shanghai, China, April 10-15, 2011

J. Banks, J. S. Carson II, B. L. Nelson, D. M. Nicol, Discrete-event system simulation, Prentice Hall, fourth edition, 2005

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