An Adaptive Wi-Fi Indoor Localization Scheme using Deep Learning

Indoor localization is an important issue for many indoor applications. Many deep learning-based indoor localization schemes have been proposed. However, these existing schemes cannot adjust according to different environment. To improve the existing schemes, a novel indoor localization scheme, which can adaptively adopt the proper fingerprint database according to the collected signals, is proposed in this paper. The experimental results show that the proposed scheme can reduce the localization error.