A grouping genetic algorithm for the microcell sectorization problem

  • Authors:

  • Evelyn C. Brown;Mark Vroblefski

  • Affiliations:

  • Department of Business Information Technology, Virginia Tech, 1007, Pamplin Hall 0235, Blacksburg, VA 24061, USA;Department of Business Information Technology, Virginia Tech, 1007, Pamplin Hall 0235, Blacksburg, VA 24061, USA

  • Venue:
  • Engineering Applications of Artificial Intelligence
  • Year:
  • 2004

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Abstract

The number of wireless users has steadily increased over the last decade, leading to the need for methods that efficiently use the limited bandwidth available. Reducing the size of the cells in a cellular network increases the rate of frequency reuse or channel reuse, thus increasing the network capacity. The drawback of this approach is increased costs associated with installation and coordination of the additional base stations. A code-division multiple-access network where the base stations are connected to the central station by fiber has been proposed to reduce the installation costs. To reduce the coordination costs and the number of handoffs, sectorization (grouping) of the cells is suggested. We propose a dynamic sectorization of the cells, depending on the current sectorization and the time-varying traffic. A grouping genetic algorithm is proposed to find a solution which minimizes costs. The computational results demonstrate the effectiveness of the algorithm across a wide range of problems. The GGA is shown to be a useful tool to efficiently allocate the limited number of channels available.