Research On Intelligent Optimization Algorithm Of Gsm Network

As the fast development of GSM networks, the competition between Service Providers becomes more and more fierce, and the demand of users on the network quality improves deeply. Therefore, the optimization of GSM networks becomes one of the most important tasks of Service Providers.GSM network optimization aims data acquisition, data analysis to identify the reasons that affect the quality of network operation and parameter adjustments and take some of the technical means to make the network run at their best to the network that officially put into operation. Therefore, it gives the existing network resources to get the best benefits, and also to put forward reasonable proposals for future maintenance and planning and construction of the network. Among it, the optimization of GSM network power is an important method in GSM network optimization, for it has many advantages:it costs no special investment; the whole process is fairly fast and convenient; and the adjustments of network parameters is quite minor.This paper is on three intelligent optimization algorithms, including Ant colony algorithm, Particle Swarm Optimization and Simulated Annealing, to optimize the GSM network power. Based on the principle of the three optimization algorithms, it sets the network coverage as the target function, and it configures new values of network power and acquires the target value (network coverage). Through the process of iteration, it acquires the optimized network coverage as the optimized value. Through the three simulation experiments, there are three optimized data. This paper gives the result of comprehensive comparison of the three optimized data on both network coverage and running time of the optimization process.