6G assistive ultra-accurate indoor localization

Abstract

Indoor localization is a critical area of research with significant global interest, driven by the need for precise navigation in complex indoor environments. The potential of future 6G networks, utilizing high frequencies with extremely short wavelengths can offer bright future for achieving highly accurate indoor localization. These high frequencies enable precise localization capabilities that surpass current technologies, making 6G a potential source for next-generation indoor navigation.

This thesis focuses on the Adaptive Reflection Tracking Based Indoor Positioning (ARTBIP) technique to enhance the precision of indoor localization for robotic applications. ARTBIP dynamically adjusts the boundaries of the indoor environment by estimating Last Reflection Points (LRP) of RF signals. As the robot moves, continuous monitoring of the LRP ensures precise localization. Using real-time LRP monitoring, ARTBIP algorithm significantly improves localization accuracy. This thesis first evaluates the effectiveness of ultra-high frequency 6G network carriers in achieving localization accuracy comparable to the wavelength of the carrier signal and then explores its potential in enhancing the performance of existing localization techniques using primary robotics sensors.