Optimization of Minimum Signal Coverage Path in Communication Node Network Based on Improved Ant Colony Algorithm

This paper proposes an optimization scheme based on the improved ant colony algorithm for the minimum signal coverage path (MCP) problem in the communication node network. MCP is similar to the minimum exposed path (MEP) problem in the sensor network. Both are committed to finding paths with weaker signals in the network, but MCP pays more attention to the strength and attenuation of signal transmission. The traditional ant colony algorithm has limitations in dealing with signal coverage path optimization. It does not fully consider the signal strength attenuation and is prone to fall into local optimality. The improved ant colony algorithm in this paper introduces signal attenuation factors and multi-path selection mechanisms, so that ants can comprehensively consider the signal transmission quality when selecting paths, and enhance the algorithm's adaptability in different signal coverage areas. Through simulation experiments, the influence of the number of communication nodes, signal coverage angle and node distribution on the minimum signal coverage path is analyzed. Experimental results show that the improved ant colony algorithm is better than the original algorithm under different node layouts, which can effectively reduce signal attenuation and improve path optimization effect.