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Allocation Optimization Based on Multi-population Genetic Algorithm for D2D Communications in Multi-services Scenario

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Machine Learning and Intelligent Communications (MLICOM 2017)

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Abstract

For D2D Communications in Multi-services scenario, fast resource allocation optimization is a crucial issue. In this paper, a resource allocation optimization method based on the multi-population genetic algorithm for D2D communications in Multi-services scenario is proposed. Due to the interference between the cellular user equipment (CUE) and D2D user equipment (DUE) which share the same frequency, the complexity of resource allocation increases. Firstly, the interference model of D2D communications is analyzed. Then the resource allocation problem is formulated and discussed. Next, a resource allocation scheme based on Multi-population genetic algorithm is presented. Finally, the analysis and simulation results show the Multi-population genetic algorithm can converge faster compared with standard genetic algorithm. Therefore, the Multi-population genetic algorithm is more suitable to the Multi-services scenario where the data rate demand varies quickly and frequently.

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Acknowledgements

This work was supported in part by “Key technology integration and demonstration of optimum dispatching of pumping stations of east route of South-to-North Water Diversion Project” of the National Key Technology R&D Program in the 12th Five-year Plan of China (2015BAB07B01), “the Fundamental Research Funds for the Central Universities (No. 2017B14214)”, the Project of National Natural Science Foundation of China (61301110), the Project funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions.

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Authors and Affiliations

  1. College of Computer and Information Engineering, Hohai University, Nanjing, 210098, China

    Xujie Li, Xing Chen, Ying Sun, Ziya Wang & Chenming Li

  2. Hubei Key Laboratory of Intelligent Wireless Communications, South-Central University for Nationalities, Wuhan, 430074, China

    Xujie Li

  3. Talent Science and Technology Co., Ltd., Nanjing, 211800, China

    Siyang Hua

Authors
  1. Xujie Li
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  2. Xing Chen
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  3. Ying Sun
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  4. Ziya Wang
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  5. Chenming Li
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  6. Siyang Hua
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Corresponding author

Correspondence to Xujie Li .

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Editors and Affiliations

  1. Harbin Institute of Technology, Harbin, Heilongjiang, China

    Xuemai Gu

  2. Harbin Institute of Technology, Weihai, Heilongjiang, China

    Gongliang Liu

  3. Shandong University, Weihai, Heilongjiang, China

    Bo Li

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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Li, X., Chen, X., Sun, Y., Wang, Z., Li, C., Hua, S. (2018). Allocation Optimization Based on Multi-population Genetic Algorithm for D2D Communications in Multi-services Scenario. In: Gu, X., Liu, G., Li, B. (eds) Machine Learning and Intelligent Communications. MLICOM 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 227. Springer, Cham. https://doi.org/10.1007/978-3-319-73447-7_4

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  • DOI: https://doi.org/10.1007/978-3-319-73447-7_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-73446-0

  • Online ISBN: 978-3-319-73447-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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