A User Demand Driven Approach for 5G Base Station Location Selection

With the continuous development and rapid popularization of 5G networks, the number of user devices and potential demand is increasing sharply. However, the high frequency of 5G signals leads to significant propagation losses. In order to achieve broader coverage of user devices, it is necessary to optimize existing 5G base station sites or guide the selection of new base station sites with low cost and high efficiency. The state-of-the-art methods for site selection mostly use heuristic algorithms to optimize the sites. However, the convergence time increases exponentially with the increase of the number of possible 5G base station sites, bringing many challenges for the site optimization. Therefore, we propose the method of selecting 5G base station sites based on user demand points to sufficiently consider the communications among users. Specifically, the planning area gridding method is proposed to reduce the time complexity of computation for user demand points covered by base stations. Then, the concept of separate degree among base stations is proposed and measured based on the number of user demand points covered by the base station. We give the objective function that satisfies the submodularity and the greedy algorithm to obtain the optimal scheme of base station site selection. Experimental results show that the proposed method outperforms the comparative algorithms on all evaluation metrics, and can effectively improve the coverage of 5G base station signals. In the same base station planning area, our proposed method achieves the maximum coverage rate with the minimum number of 5G base stations, thereby effectively reducing the construction cost of 5G base stations.