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The coverage area of base stations has shrunk due to the rapid growth of 5G technology in China, but the quantity of base stations needed to cover the same region has significantly grown. For a significant number of dispersed poor coverage locations to be adequately covered by existing base stations, additional base stations are needed. This study incrementally optimizes the placement and design of a new base station in order to save costs while taking into account the base station's various coverage areas. Regional clustering of weak coverage points is done to address the coverage issue with such places. The new base station should initially cover the poor coverage points with big service volumes since the base station's coverage area is circular and the service volume of the weak coverage points covered is not less than 90% of the total number. A two-dimensional array is used to describe the position of the weak coverage point, the traffic, the location of the existing base station, and the location and type of the new base station. The computation is simplified by first excluding the fence points that are too close to the current base station and then optimizing the remaining fence points to determine if the base station can be erected and what kind of base station.C language programming was used to build relevant software to deal with this problem, and the data was cleaned and the center point of the grid was divided into 60×60 and 200×200 regions. Through programming operation, the optimization setting result of the base station was as follows: Construction of 2178 microbase stations and 1 macro base station, which together cover 90.0055795% of the total traffic, at a cost of 2188 units. Through the distribution of only micro base stations, the optimization model is established. After the improvement of the program and the cleaning and screening of the data again, the optimal base station setting result is finally obtained: the construction of 2187 micro base stations costs 2187 units, and these base stations cover the total business volume of 90.0181713819829%.
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