Scenario modeling-aided AP placement optimization method for indoor localization and network access

Owing to the ubiquity of wireless networks and the popularity of WiFi infrastructures, received signal strength (RSS)-based indoor localization systems have received much attention. The placement of access points (APs) significantly influences localization accuracy and network access. However, the indoor scenario and network access are not fully considered in previous AP placement optimization methods. This study proposes a practical scenario modeling-aided AP placement optimization method for improving localization accuracy and network access. In order to reduce the gap between simulation-based and field measurement-based AP placement optimization methods, we introduce an indoor scenario modeling and Gaussian process-based RSS prediction method. After that, the localization and network access metrics are implemented in the multiple objective particle swarm optimization (MOPSO) solution, Pareto front criterion and virtual repulsion force are applied to determine the optimal AP placement. Finally, field experiments demonstrate the effectiveness of the proposed indoor scenario modeling method and RSS prediction model. A thorough comparison confirms the localization and network access improvement attributed to the proposed anchor placement method.