Indoor Access Points Location Optimization Using Differential Evolution

Wireless indoor positioning systems have become very popular and attractive in recent years. These systems have been successfully used in many fields such as asset tracking and inventory management, and location fingerprinting schemes are the most promising technique because of technical restrictions. However, how to optimize the location of access points to improve the positioning accuracy is still a challenging and difficult problem because of the complexity of indoor radio propagation environments. In this paper, we firstly discussed the indoor radio propagation model and proposed a novel optimization model for access points location optimization in which the Euclidean distance of received signal strength array among all the sampling points should be maximize in order to increase the differentia and diversity of the signal strength array, and thus improve the positioning accuracy of location fingerprinting schemes. Then we presented the Differential Evolution algorithm which was used to optimize the proposed problem, and the experimental testbed, experimental results and analysis were discussed. Experimental results show that the proposed model for access points location optimization can improve the positioning accuracy remarkably. Finally, we summarized the paper and gave possible future directions for research on access points location optimization for indoor environments.