Genetic Algorithm And Its Application On Optimization Of Placing Repeater In GSM Network

With the explosive increase of Chinese mobile subscribers and the burgeoning of Chinese communication industry, the speed of mobile system construction is become more and more faster. GSM network plays an important role in mobile communication systems nowadays. During the development of the mobile communication, the competition of mobile communicate markets is firece and the subscribers want to enjoy the mobile service of good quality at anytime and anywhere. The quality of network becomes the key whether the network operator can occupy the market and succeed. Therefore the service providers start to deploy the repeaters outdoors, indoors and underground where the mobile signal can not cover previously.The final aim of network optimization is to keep the network in the best running state and get the best economic benefits. During the network optimization using the repeater, the network coverage and the financial cost are two evaluation criterias of the network and also the survival of mobile service provider.Since basic genetic algorithm optimization process "direction" and easily "premature" phenomenon, the large amount of calculation and easily into a "local optimal solution", the improved genetic algorithm operators are used in this paper. The introduction of high quality and selection strategy, simplex crossover operator, fitness density variation found the median and climbing algorithm method were also inspired to accelerate the convergence without leading to premature. Finally the improved Genetic Algorithms were applied to solve the repeator placement in the paper to accelerate the speed and avoid premature two.The object function in the optimal algorithm is defined according to the two important keys of GSM network including network coverage,portfolio cover and the financial cost of the repeater. This paper combined specific parameters of related of GSM system with object function, optimized the placement of repeater using improved genetic algorithm, and found an availavle plan of repeater placement. It abtained higher coverage ratio and with lower cost, and obtained coverage result of a repeater which is in a given area by simulation of the computer. The sinmulation resuilts showed that the coverage radtio can reach above 90% for the repeaters which is in a given area with less quantity.