# Research on Location Selection Model of 5G Micro Base Station Based on Smart Street Lighting System
## 5 Simulation and Analysis
### Simulation Experiment  
Our method was implemented using the MATLAB toolbox on a GeForce RTX 3090 Ti. According to previous regulations, the base station construction coverage rate should not be less than 90% [31; 32]. In the process of model solving, the coverage radius of the 5G micro base station is defined as \(r=150\) m, and the coverage requirement is defined as \(\gamma=90\%\). The final visualization result of location selection is shown in Figure 4, where the red serial number represents the road section number. The average distance of light poles is 25-30 m for each road section, and the yellow point represents the location of the 5G micro base station.  
The analysis of the location selection results of the three functional areas is shown in Table 3. The results are above 90% and meet the basic coverage requirements. The  
Figure 4: Visualization of location selection results. (**a**) Commercial area location selection results. (**b**) Residential area location selection results. (**c**) Industrial area location selection results. Red numbers represent alternative points, and yellow dots represent site selection results.  
minimum number of 5G micro base stations in the commercial area with the smallest area can be built to meet the basic coverage requirements. With the increase in location selection area, the number of base station construction also increases under the same coverage requirements. In addition, under the coverage requirement of 90%, the combined ratio of the three functional areas has reached 100%, indicating that there is no need to build a single independent pole for the 5G micro base station, reducing the engineering cost.  
The difficulty coefficient of location selection affects the system coordination degree of location selection results. The commercial area has a high density of light poles, excellent infrastructure, and the lowest difficulty in location selection. The 5G micro base station is easy to produce coupling effect with the carrying equipment and achieves a 100% coupling ratio and 97.51% of the highest subsystem coordination degree. However, due to the variety of equipment mounted on the light pole, the unification ratio drops to 70.43%, which reduces the aesthetics of the city and increases the production cost of equipment. In residential areas, the density of light poles is lower than that of commercial areas, so the location selection is more complex, resulting in a lower degree of subsystem coordination. In the industrial area, it has the characteristics of a wide area and few light poles, which increases the difficulty of location selection. Due to the insufficient infrastructure carried by light poles, the ratio of coupling poles decreases, which is not conducive to reducing the synergistic effect between subsystems. The final optimal location selection scheme only achieves a 62.5% coupling rate and 82% subsystem coordination degree. In conclusion, the subsystem coordination degree of the three functional areas is greater than 80%, indicating that the location selection model of this study considers the construction cost and relevance of location selection schemes. On the premise of meeting the coverage requirements, the synergistic effect between smart light pole subsystems can be played, thereby reducing construction costs, improving service efficiency, and providing an effective location selection scheme for the intelligent construction of smart light poles in smart cities.