Layout optimization scheme for coexistence of multiple coverage capabilities in base stationsBased on genetic algorithm

Abstract

With the development of 5G technology, communication networks have become increasingly complex, leading to a continuous growth in the number of base stations. While this has resulted in faster speeds, lower latency, and greater capacity, it has also presented a pressing issue: weak coverage points, areas with weak signal radiation from base stations. To address this challenge, this paper proposes a layout optimization scheme for the coexistence of base stations with multiple coverage capabilities, based on a genetic algorithm. The scheme considers the rational deployment of various types of base stations (represented as macro base stations and micro base stations in the paper) to improve the situation of weak coverage points. The specific steps of the optimization layout scheme include initializing existing base station coverage, calculating distances to weak coverage points, selecting new base station locations, updating data, and analyzing calculations. The final output includes the coordinates and types of new base stations needed. Through model simulation, the proposed optimization layout scheme can consider cost, coverage effectiveness, and threshold constraints while accommodating various requirements. Additionally, the scheme is highly applicable and can be integrated with computer analysis software. Finally, a dialectical analysis of the model is conducted, recognizing the flexibility and practicality advantages of the layout optimization scheme based on genetic algorithms, while acknowledging potential limitations such as overly idealistic assumptions.