Self-optimization of power parameters in WCDMA networks

Abstract

Network optimization is used by operators to maximize return on investment and to ensure customer satisfaction with the quality of the delivered service. Coverage and capacity are the most important characteristics of any cellular network. In WCDMA networks, the pilot signal of a cell is used to determine the cell size, hence it can be used to determine the coverage area of the cell. Increasing or reducing the cell pilot power increases or reduces the cell size respectively and hence pilot power can be used to balance load among neighboring cells. As networks continue to evolve, the frequency of optimization and number of tunable parameters continues to increase making manual optimization challenging. This paper presents a practical solution to the pilot power optimization problem in WCDMA networks and addresses the issue of rising optimization complexity by presenting a self-optimization based algorithm for tuning pilot power. When running in closed loop, the algorithm can be used to autonomously optimize pilot power and load balance traffic in the network. When scheduled or triggered manually, the algorithm can also be used to improve network capacity in areas expecting high traffic load during a certain time for example during social gatherings.