Intelligent AP selection for indoor positioning in wireless local area network

Abstract

Indoor positioning system in wireless local area network (WLAN) has been receiving increasing interest in pervasive computing applications. To keep balance between energy consumption on client device and positioning accuracy, AP selection strategy is always proposed to select the most discriminant APs for positioning. In this paper, we propose an intelligent AP selection method based on joint location information gain. In contrast to traditional AP selection methods which measure the discriminant ability of APs independently, we consider it jointly. By considering the correlation of the discriminant ability between different APs, more accurate measure of the discriminant ability can be taken. Besides, support vector regression (SVR) positioning algorithm is combined to estimate the location. Experiments are carried in a realistic WLAN indoor environment. Experimental results show that, by using the intelligent AP selection method, the proposed positioning algorithm maintains a high-level accuracy while reducing the energy consumption on client device significantly.