Automatic Frequency Planning & Optimization

Powerful Essays
Automatic Frequency Planning and Optimization
Algorithm for Cellular Networks
Muhammad Umair, Waleed Bin Shahid, Masab Javed Abbasi,
Department of Electrical Engineering
Royal Institute of Technology (KTH)
SE100-44 Stockholm, SWEDEN
E-mail: mumair@kth.se, waleed.shahid@mcs.edu.pk , masab.abbasi-pc@telenor.com.pk
Abstract— Frequency planning in ever growing cellular networks is an extremely arduous task. Any effort to lay down manual frequency plans promulgates inefficiency in the cellular radio systems. The extensive deployment and penetration of cellular networks necessitate the need to carry out automatic frequency planning. This paper presents a novel and ingenious algorithm for automatic generation and optimization of the frequency plan whereby curtailing the intra-system interference levels within the acceptable ranges of the key performance indicators (KPI’s) defined for any real time cellular network. The automatic frequency planning and optimization has been done using the concept of Inter-Cell
Dependency Matrix (ICDM) which contains cell correlations in terms of the affect one cell has on the other primarily with regards to the co-channel interference. The proposed algorithm was simulated in MATLAB. It has been set forth and tested using inputs from live network data. It has been found to satisfy the verifiable network performance metrics.
Index Terms—Automatic Frequency Planning, Inter Cell dependency matrix, Intra-system Interference, Co-channel
Interference, Traffic based ICDM.

I.

INTRODUCTION

Cellular telephony has rapidly evolved as the prime form of wireless communication over the last decade. The widespread deployments of cellular networks derive motivation from the need to provide mobile telephony service, so as to enhance the capacity in terms of the number of users. However, radio spectrum is a scarce resource, which inhibits the indefinite growth of user-based capacity [1]. As a consequence, the radio



References: Frequency Planning Algorithm in a Real Land Mobile Radio System Design”, IEEE MELECON 2002, May 7-9, 2002, Cairo, Egypt. 108–120, 2007, © Springer-Verlag Berlin Heidelberg 2007. Dependency Matrix in a GSM network”, Vehicular Technology Conference, 1999 Phone Networks”. July10, 1997. Cellular Communication System,” in IEEE International Conference on Communications (ICC), 2009. wireless mobile networks. IEEE Transactions on Vehicular Technology 54 (2005) 1887–1895. computing in telecommunication network design: A survey. In Revision (2006). [14] Lee, W.C.Y., Mobile Commnications Design Funbntals, John Wiley & Sons, inc, 1993. Conf. on Evolutionary Computation.(1995) 539–544 [16] Hale, W.K.: Frequency assignment: Theory and applications. Proceedings of the IEEE 68 (1980) 1497–1514 [17] Aardal, K.I., van Hoesen, S.P.M., Koster, A.M.C.A., Mannino, C., [18] Smith, D.H., Allen, S.M., Hurley, S.: Characteristics of good metaheuristics algorithms for the frequency assignment problem. Annals of Operations Research 107 (2001) 285–301 2G/2.5G/3G... Evolution to 4G. Wiley (2004) 21–54 [20] GAMST, A

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