Indoor WLAN Deployment Optimization Based on Error Bound of Neighbor Matching

In this paper, we propose a novel indoor Wireless Local Area Network (WLAN) deployment optimization approach based on the error bounds of Neighbor Matching Algorithms (NMAs). We derive out the closed-form solution to the localization errors of NMAs with respect to the environmental size, interval of Reference Points (RPs), number of neighbors, and locations of Access Points (APs). Based on the requirement of localization precision, as well as networking overhead, we optimize the networking parameters, like the interval of RPs, number of neighbors, and locations of APs. Finally, the extensive experiments are conducted to demonstrate that the proposed approach can effectively improve the localization precision of NMAs in indoor WLAN environment.