5G Private Network Deployment Optimization Based on RWSSA in Open-Pit Mine
Zhaozhao Chang, Qinghua Gu, Caiwu Lu, Yanhong Zhang, Shunling Ruan, Song Jiang
Abstract
5G communication network is vital to the intelligent and unmanned technology of open-pit mine, but the high cost of 5G base station deployment will bring huge cost increases to mining enterprises. Thus, this article proposes an improved sparrow search algorithm (SSA) using random walk strategy (RWSSA) to optimization the distribution and signal coverage of 5G base stations in open-pit mine. In order to verify the performance of the algorithm, the SSA, the modified ant lion optimizer, the particle swarm optimization, and the RWSSA were used to compare and analyze the accuracy and speed of the algorithm in solving high dimensionality benchmark functions, respectively. The dimensions used in the test are 30, 100, and 500 dimensions. After that, four algorithms were applied to a real example to optimize the deployment of 5G base stations, including macrobase stations and microbase stations. RWSSA has very good performance in terms of performance and practical application. Therefore, RWSSA is more suitable for the application of 5G base station distribution optimization in open-pit mines.