Sixth-generation (6G) mobile communication networks are expected to have dense
infrastructures, large antenna size, wide bandwidth, cost-effective hardware, diversified …

With the rapid development of wireless communication technology, various indoor location‐
based services (ILBSs) have gradually penetrated into daily life. Although many other …

This article proposes recurrent neural networks (RNNs) for the WiFi fingerprinting indoor
localization. Instead of locating a mobile user's position one at a time as in the cases of …

In the recent past, we have witnessed the adoption of different machine learning techniques
for indoor positioning applications using WiFi, Bluetooth and other technologies. The …

With the rapid development of Internet of Things (IoT) technology, location-based services
have been widely applied in the construction of smart cities. Satellite-based location …

With the broad deployment of Wi-Fi networks, the Received Signal Strength (RSS) based Wi-
Fi indoor localization has attained much interest of both academia and industry. At present …

Understanding and predicting cellular traffic at large-scale and fine-granularity is beneficial
and valuable to mobile users, wireless carriers, and city authorities. Predicting cellular traffic …

Indoor localization has the capability to change the way of providing location-based services
in a closed environment and has more potential than that of GPS if the present shortcomings …

With widely deployed WiFi network and the uniqueness feature (fingerprint) of wireless
channel information, fingerprinting based WiFi positioning is currently the mainstream indoor …

This paper proposes a soft range limited K-nearest neighbors (SRL-KNNs) localization
fingerprinting algorithm. The conventional KNN determines the neighbors of a user by …