Parameter Study for Differential Evolution Using a Power Allocation Problem Including Interference Cancellation

Abstract

The performance of evolutionary algorithms is strongly dependent on the setting of control parameters. Not only the convergence speed is influenced, but also if the optimum of a function is reached at all. For differential evolution premature convergence or even stagnation can occur due to certain parameter settings. In this paper a parameter study for differential evolution is conducted. As basis for the examination a real-world problem is employed that consists of optimizing the power allocation for a CDMA (code division multiple access) system. For the CDMA system interference cancellation methods are applied as the detection performance is significantly degraded by multi-user interference. The convergence of the interference cancellation method establishes a constraint for the single-objective optimization problem. Optimization results for both parallel and successive interference cancellation are given. The findings of the parameter study are compared with results from literature, and recommendations concerning settings of DE control parameters are given.