Abstract
This paper addresses the displacement of a base station with optimization approach. A genetic algorithm is used as optimization approach. A new representation that describes base station placement, transmitted power with real numbers and new genetic operators is proposed and introduced. In addition, this new representation can describe the number of base stations. For the positioning of the base station, both coverage and economy efficiency factors were considered. Using the weighted objective function, it is possible to specify the location of the base station, the cell coverage and its economy efficiency. The economy efficiency indicates a reduction if the number of base stations for cost effectiveness. To test the proposed algorithm, the proposed algorithm was applied to homogeneous traffic environment. Following this, the proposed algorithm was applied to an inhomogeneous traffic density environment in order to test it in actual conditions. The simulation results show that the algorithm enables the finding of a near optimal solution of base station placement and it determines the efficient number of base stations. Moreover, it can offer a proper solution by adjusting the weighted objective function.
Please use the following format when citing this chapter: Choi, Y. S., Kim, K. S., Kim, N., 2007, in IFIP International Federation for Information Processing, Volume 245, Personal Wireless Communications, eds. Simak, B., Bestak, R., Kozowska, E., (Boston: Springer), pp. 217–229.
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Keywords
- Genetic Algorithm
- Genetic Operator
- Traffic Density
- Personal Wireless Communication
- Base Station Location
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Choi, Y.S., Kim, K.S., Kim, N. (2007). The Positioning of Base Station in Wireless Communication with Genetic Approach. In: Bestak, R., Simak, B., Kozlowska, E. (eds) Personal Wireless Communications. IFIP — The International Federation for Information Processing, vol 245. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-74159-8_21
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DOI: https://doi.org/10.1007/978-0-387-74159-8_21
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