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Research on Site Planning of Mobile Communication Network

Computers, Materials & Continua 2024年第8期80卷 3243-3261页

作者： Jiahan He Guangjun Liang Meng Li KefanYao Bixia Wang Lu Li Department of Computer Information and Cyber Security Jiangsu Police InstituteNanjing210000China Engineering Research Center of Electronic Data Forensics Analysis Nanjing210000China Key Laboratory of Digital Forensics Department of Public Security of Jiangsu ProvinceNanjing210000China Basic Course Teaching and Research Department Jiangsu Police InstituteNanjing210000China Communication and Signal College Nanjing Railway Vocational and TechnicalNanjing210000China

In this paper,considering the cost of base station,coverage,call quality,and other practical factors,a multi-objective optimal site planning scheme is ***,based on practical needs,mathematical modeling methods were used to establish mathematical expressions for the three sub-objectives of cost objectives,coverage objectives,and quality ***,a multi-objective optimization model was established by combining threshold and traffic volume *** order to reduce the time complexity of optimization,a non-dominated sorting genetic algorithm(NSGA)is used to solve the multi-objective optimization problem of site ***,a strategy for clustering and optimizing weak coverage areas was *** order to avoid redundant neighborhood retrieval during cluster expansion,the Fast Density-Based Spatial Clustering of Applications with Noise(FDBSCAN)clustering method was *** different sub-objectives as the main objectives,this paper obtained the distribution map of weak coverage areas before and after the establishment of new base stations,as well as relevant site planning maps,and provided three planning schemes for different main *** simulation results show that the traffic coverage of the three station planning schemes is above 90%.The change in the main optimization objective will result in a significant difference between the cost of the three solutions and the coverage of weak coverage points.

关键词： siting of station multi-objective optimization genetic algorithm NSGA general greed FDBSCAN cluster

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