Abstract
In recent years, the transmission rate of mobile network becomes insufficient to serve numerous mobile users. Relay technique has been proposed to improve the data rate of mobile networks for many years. In the paper, the planning problem of heterogeneous cellular network is defined and limited in two-hop relaying. The defined problem aims to tackle with three objective functions at the same time. A meta-heuristic planning algorithm is proposed based on Ant Colony Optimization (ACO) algorithm. The proposed ACO-based algorithm optimizes the placement results of macrocells, microcells and femtocells. In the simulation-based result and analysis, the ACO-based algorithm yields the higher capacity and more covered users with the lowest construction cost compared to the two heuristic algorithms, i.e., Top-Down and Bottom-Up algorithms.
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Acknowledgements
This work was financially supported from the Young Scholar Fellowship Program by Ministry of Science and Technology (MOST) in Taiwan, under Grant MOST108-2636-E-003-001, and was partly funded by the MOST in Taiwan, under grant MOST107-2221-E-259-005-MY3.
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Tseng, FH., Kao, FY., Liang, TT., Chao, HC. (2020). Ant Colony Optimization Algorithm for Network Planning in Heterogeneous Cellular Networks. In: Pan, JS., Lin, JW., Liang, Y., Chu, SC. (eds) Genetic and Evolutionary Computing. ICGEC 2019. Advances in Intelligent Systems and Computing, vol 1107. Springer, Singapore. https://doi.org/10.1007/978-981-15-3308-2_2
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DOI: https://doi.org/10.1007/978-981-15-3308-2_2
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