Abstract
To meet the requirements of high system capacity and coverage of 5G network, ultra-dense network is viewed as the key technology for networking evolution. And for densely deployed small cell network, self-optimization is crucial in the aspect of reducing the cost of network management while optimizing the network performance. This paper focuses on the coverage and capacity optimization, proposing a mathematical combined optimization function to balance the conflicting key performance indicators. And under this model, we propose the tabu search algorithm for generating new antenna transmit power to optimize the performance. Simulation results show that our proposed algorithm gets significant improvement in network performance and outperforms the adaptive simulated annealing in convergence speed while optimizing.
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Acknowledgments
This work was supported by the China’s 973 project (No. 2012CB31600), the China’s 863 Project (No. 2014AA01A706), the National S&T Major Project (No. 2014ZX03004003), Science and Technology Program of Beijing (No. D161100001016002), S&T Cooperation Projects (No. 2015DFT10160B), and by State Key Laboratory of Wireless Mobile Communications, China Academy of Telecommunications Technology (CATT).
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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Su, X., Lin, X., Zeng, J., Xiao, C. (2018). Coverage and Capacity Optimization Based on Tabu Search in Ultra-Dense Network. In: Chen, Q., Meng, W., Zhao, L. (eds) Communications and Networking. ChinaCom 2016. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 210. Springer, Cham. https://doi.org/10.1007/978-3-319-66628-0_6
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DOI: https://doi.org/10.1007/978-3-319-66628-0_6
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