Research and Implementation of 5G Base Station Location
Based on factors such as base station construction cost, signal coverage, and Euclidean distance between base stations, this paper constructs a multi-objective planning and loca-tion model
(2) Constraints: Euclidean distance between base stations, whether the base station covers the test point, whether the coverage reaches the standard, etc. (3) Output: the specific planning point of the base station, the simulation diagram of the base station coverage test point.
Moreover, we propose a dynamically adjusted quantum genetic algorithm (DAQGA) to optimize base station layout, with coverage and construction cost as objective functions. A signal reception strength metric is introduced to evaluate the effectiveness of the optimal layout.
To obtain base station deployment parameters that better reflect real-world conditions, this section introduces a series of constraints, mainly including the candidate locations for base stations, the height of ground base stations, the height of rooftop base stations, and the distance between base stations.
Especially with the development and promotion of national 5G technology, the construction of 5G base stations is an important part of the future communication infrastructure. Therefore, base station site selection will become an important work of base station construction.
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