Intelligent coverage optimization with multi-objective genetic algorithm in cellular system

A multi-objective genetic algorithm is proposed in this paper for intelligent coverage optimization according to users' requirements in cellular mobile network. Based on the coverage balance between uplink and downlink, status of cell coverage is evaluated through the measurement data reported by mobile stations, and then an adjustment scheme is generated to optimize the downlink coverage by switching the cells on or off and tuning the transmitting power of base stations periodically. The simulation results show that network performances of downlink insufficient coverage and excessive coverage could be improved after the optimization using our algorithm.