Open Access

ARTICLE

Research on Site Planning of Mobile Communication Network

by Jiahan He¹, Guangjun Liang^1,2,3,*, Meng Li⁴, Kefan Yao¹, Bixia Wang¹, Lu Li⁵

1 Department of Computer Information and Cyber Security, Jiangsu Police Institute, Nanjing, 210000, China
2 Engineering Research Center of Electronic Data Forensics Analysis, Nanjing, 210000, China
3 Key Laboratory of Digital Forensics, Department of Public Security of Jiangsu Province, Nanjing, 210000, China
4 Basic Course Teaching and Research Department, Jiangsu Police Institute, Nanjing, 210000, China
5 Communication and Signal College, Nanjing Railway Vocational and Technical, Nanjing, 210000, China

* Corresponding Author: Guangjun Liang. Email:

Computers, Materials & Continua 2024, 80(2), 3243-3261. https://doi.org/10.32604/cmc.2024.051710

Received 13 March 2024; Accepted 18 July 2024; Issue published 15 August 2024

Abstract

In this paper, considering the cost of base station, coverage, call quality, and other practical factors, a multi-objective optimal site planning scheme is proposed. Firstly, 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 objectives. Then, a multi-objective optimization model was established by combining threshold and traffic volume constraints. In 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 planning. Finally, a strategy for clustering and optimizing weak coverage areas was proposed. In order to avoid redundant neighborhood retrieval during cluster expansion, the Fast Density-Based Spatial Clustering of Applications with Noise (FDBSCAN) clustering method was adopted. With 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 objectives. The 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.

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Keywords

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