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Optimal WCDMA network planning by multiobjective evolutionary algorithm with problem-specific genetic operation

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Abstract

The wideband code division multiple access (WCDMA) network planning problem requires to determine the location and the configuration parameters of the base stations (BSs) so as to maximize the capacity and minimize the installation cost. This problem can be formulated as a complex set covering problem. Compared to the classical set covering problems, the coverage area of each BS is unknown in advance. This makes that the selection of each BS location and configuration parameters is determined by the location and configuration parameters of the neighbor BSs. Accordingly, we will conduct a competition and cooperation model based on the re-covered area of the BSs to measure the relationship of the BSs. Then, an efficient genetic operation based on this model is proposed to generate new-quality solutions. Further, four BS configuration parameters, i.e., the antenna height, antenna tilt, sector orientation and pilot signal power, are taken into account as well. Since there are too many combination levels of the configuration parameters, an encoding method based on orthogonal design is presented to reduce the search space. Subsequently, we merge the proposed encoding method and genetic operation into the multiobjective evolutionary algorithm-based decomposition (MOEA/D-M2M) to solve the WCDMA network planning problem. Simulation results show the efficacy of the proposed encoding and genetic operation in comparison with the existing counterpart.

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Acknowledgments

This work was supported by the Natural Science Foundation of China (61273192, 61333013, 61272366), the Natural Science Foundation of Guangdong Province (S2012010008813, S2011030002886), the projects of Science and Technology of Guangzhou Province (2014J4100209), and the Faculty Research Grant of Hong Kong Baptist University with the Project Code: FRG1/14-15/041.

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Authors and Affiliations

  1. Guangdong University of Technology, Guangdong, China

    Fangqing Gu, Hai-lin Liu & Shengli Xie

  2. Department of Computer Science, Hong Kong Baptist University, Hong Kong SAR, China

    Fangqing Gu & Yiu-Ming Cheung

  3. United International College, Beijing Normal University–Hong Kong Baptist University, Zhuhai, China

    Yiu-Ming Cheung

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  1. Fangqing Gu
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  2. Hai-lin Liu
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  4. Shengli Xie
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Correspondence to Hai-lin Liu.

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Gu, F., Liu, Hl., Cheung, YM. et al. Optimal WCDMA network planning by multiobjective evolutionary algorithm with problem-specific genetic operation. Knowl Inf Syst 45, 679–703 (2015). https://doi.org/10.1007/s10115-014-0799-y

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  • DOI: https://doi.org/10.1007/s10115-014-0799-y

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