Deep Learning-Based Indoor Localization Using Received Signal Strength and Channel State Information

Learning Indoor Localization using Radio Received Signal Strength

Channel State Information Fingerprinting Based Indoor Localization: a Deep Learning Approach by

With the fast growing demand of location-based services in indoor environments, indoor positioning based on fingerprinting has attracted a lot of interest due to its high accuracy. In this thesis, we present a novel deep learning based indoor fingerprinting system using Channel State Information (CSI), which is termed DeepFi. Based on three hypotheses on CSI, the DeepFi system architecture incl...

PRIMAL: Page Rank-Based Indoor Mapping and Localization Using Gene-Sequenced Unlabeled WLAN Received Signal Strength

Due to the wide deployment of wireless local area networks (WLAN), received signal strength (RSS)-based indoor WLAN localization has attracted considerable attention in both academia and industry. In this paper, we propose a novel page rank-based indoor mapping and localization (PRIMAL) by using the gene-sequenced unlabeled WLAN RSS for simultaneous localization and mapping (SLAM). Specifically...

Emitter localization using received-strength-signal data

This paper considers a scenario in which signals from an emitter at an unknown location are received at a number of different collinear locations. The receiver can determine the received signal strength, but no other parameters of the signal. Postulating a log-normal transmission model with a constant but unknown path loss exponent and, also, an unknown transmit power and known noise variance, ...

Π8: Indoor Positioning System using WLAN Received Signal Strength Measurements

In this deliverable we provide the details of building an indoor positioning system using WLAN Received Signal Strength (RSS) fingerprints. The positioning system has been deployed at the premises of KIOS Research Center and follows a terminal-based-network-assisted architecture. In our case, users that carry a terminal (Tablet PC) are able to self-locate and positioning is performed entirely o...