Traffic adaptive channel switching with time slice based predictors

Channel switching in HSPA networks is used to reduce the channel occupancy when there is no data transfer for the given user, this way reducing battery consumption. This paper is the first dealing with another important aspect that is the CPU load on the radio network controller (RNC) caused by channel switching. This is an optimization task, in which both the channel switching and staying on the high-bandwidth channel have costs. In this paper we propose a system to minimize the costs by applying a predictor based method which uses time slice based features in order to reduce the high variance in the feature values. The proposed system is evaluated and compared to other state-of-the-art methods.