Academic Journal of Computing & Information Science, 2022, 5(8); doi: 10.25236/AJCIS.2022.050807.
Xuelei Yang, Hao Lin, Zhaoguo Wang
School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo, Shandong, China
Due to the continuous development of mobile communication technology, users' demand for communication networks is gradually increasing, and the existing base stations can no longer meet the increasing demand. The base station siting problem is to select a suitable new base station to meet the services at the weak coverage points based on the existing base stations, and to consider the signal propagation range and the sub-regional management of each weak coverage point. Firstly, it is assumed that only new base stations are established at the weak coverage points to simplify the calculation. In this paper, a multi-objective planning model based on genetic algorithm is established, and since coverage and cost are negatively correlated, the total coverage service volume and total cost are solidly used as the objective function, whether base stations are established as the decision variables, and the threshold etc. are used as the constraints to establish the optimization model, and the Pareto front is plotted, and one of the dominant solutions that meets the requirements of the topic is selected, and finally The total coverage is 91.2%, with 312 macro base stations and 8431 micro base stations.
Genetic algorithm, multi-objective optimization, greedy algorithm, density clustering, improved Dbscan algorithm
Xuelei Yang, Hao Lin, Zhaoguo Wang. Genetic algorithm-based analysis of base station siting optimization. Academic Journal of Computing & Information Science (2022), Vol. 5, Issue 8: 45-49. https://doi.org/10.25236/AJCIS.2022.050807.
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