|IEEE Wireless Communications Letters
|Zhou Baoding,Tu Wei,Mai Ke,Xue WeiXing,Ma Wei,Li Qingquan
To achieve the satisfactory performance of WiFi fingerprinting-based indoor localization, additional access point(AP) deployment is usually required in some environments. How to place these additional APs is a problem. The current AP placement methods do not consider the existing APs. In this letter, we propose a novel AP placement method for WiFi fingerprinting that considers existing APs. The parameters of the radio propagation model are first obtained based on data collected from the existing APs. Then, based on the self-learning parameters, we perform a genetic algorithm (GA)-based optimization method for AP placement. The experimental results demonstrate the effectiveness of the proposed method.