Application of Improved Ant Colony Algorithm in Automatic Recognition of Abnormal Signals in Wireless Communication Networks

Ant colony algorithm is a method that utilizes swarm intelligence to find the optimal solution. This algorithm can be used to solve a complex optimal problem with high efficiency. On this basis, this article studied a new ant based anomaly signal detection method in mobile communication networks. In wireless communication, it is necessary to effectively detect abnormal signals to ensure the normal operation of the system. Ant colony algorithm is to simulate the feeding behavior of ant colony, and find the optimal solution according to the random characteristics of ant colony and the transfer law of pheromone. This article studied an automatic recognition method for abnormal signals in wireless communication networks and applied it to wireless communication networks. By diffusing information elements, problem solving can be accelerated to obtain the optimal solution and improve solution efficiency. This project aims to enhance the efficiency of an algorithm that mimics the behavior of ant colonies to find the optimal solution. By adding multiple groups, increasing the importance of heuristic information, and dynamically updating pheromones, the algorithm's search efficiency and quality can be improved. The experiment showed that this improved algorithm performs much better than traditional ones in recognizing abnormal signals in wireless communication networks. This suggests that the improved ant colony algorithm is highly suitable for this application.