Wireless Networks

, Volume 17, Issue 3, pp 597–609 | Cite as

Evolutionary multiobjective optimization of cellular base station locations using modified NSGA-II

  • N. Lakshminarasimman
  • S. Baskar
  • A. Alphones
  • M. Willjuice Iruthayarajan
Article
First Online:

Abstract

In this paper, various parameters of cellular base station (BS) placement problem such as site coordinates, transmitting power, height and tilt angle are determined using evolutionary multiobjective algorithm to obtain better compromised solutions. The maximization of service coverage and minimization of cost are considered as conflicting objectives by satisfying inequality constraints such as handover, traffic demand and overlap. For the purpose of simulation, a 15 × 15 Km2 synthetic test system is discretized as hexagonal cell structure and necessary simulations are carried out to calculate receiving field strength at various points. The path loss is calculated using Hata model. To improve the diversity and uniformity of the obtained nondominated solutions, controlled elitism and dynamic crowding distance operators are introduced in non-dominated sorting genetic algorithm-II (NSGA-II) and are designated as modified NSGA-II (MNSGA-II). The optimal placement for BS is determined using MNSGA-II and NSGA-II. The effect of maximum number of function evaluations, handover and overlap on the performances of the algorithms is studied. A better distributed Pareto-front is obtained in MNSGA- II when compared with NSGA- II. The results reveal that, increasing of overlap percentage not only increases the coverage but also increases the overlap and handover error. The coverage percentage is indirectly proportional to the number of antennas involved in the handover constraint. The simulation results reveal that the proposed technique is more suitable for real-world BS placement problem.

Keywords

Base station placement Cellular network planning Controlled elitism Dynamic crowding distance Multiobjective optimization Non-dominated sorting genetic algorithm (NSGA-II) 
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Notes

Acknowledgments

The authors are grateful to the managements of the Thiagarajar College of Engineering, Madurai and the K.L.N. College of Engineering, Madurai for having granted permission to utilize their infrastructure facilities for the research activities. The authors are also grateful to Dr.Stephen Hurley, Reader, Department of computer science and Director of the centre of mobile communications, Cardiff University, Wales, UK for his expert guidance. The authors also show their gratitude to Bharat Sanchar Nigam Limited, Madurai for having rendered many useful discussions and provided technical clarifications.

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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • N. Lakshminarasimman
    • 1
  • S. Baskar
    • 2
  • A. Alphones
    • 3
  • M. Willjuice Iruthayarajan
    • 2
  1. 1.Department of Computer Science and EngineeringK.L.N. College of EngineeringMaduraiIndia
  2. 2.Department of Electrical and Electronics EngineeringThiagarajar College of EngineeringMaduraiIndia
  3. 3.School of Electrical and Electronic EngineeringNanyang Technological UniversityNanyang AvenueSingapore

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