AP Deployment Optimization Based on Bluetooth Fingerprint Database Discrimination

Abstract

In indoor fingerprint positioning system, Access Point (AP) deployment costs a lot of manpower and time, and the deployment efficiency of existing methods is extremely low due to the complexity and dynamics of indoor environment. In order to solve this problem, this paper proposes an optimal AP deployment algorithm. First of all, wireless signal propagation model is established from indoor environment. Then simulated fingerprint database is constructed based on initial AP deployment. Finally, greedy algorithm is selected to optimize the deployment of APs. The experimental results show that this method can be well adapted to the indoor environment with higher accuracy compared to the empirical AP deployment.