Engineers from the University of Glasgow, along with colleagues from the U.K. and Australia, have made a significant breakthrough in wireless communications that could revolutionize indoor location tracking. This development has the potential to aid emergency services in locating individuals trapped in smoke-filled buildings and provide device-assisted navigation for the blind and partially sighted. Additionally, it could enhance mobile phone signal quality indoors, eliminating the need to search for optimal spots to make calls.

The research, detailed in a new paper published in the journal Communications Engineering, focuses on improving an emerging wireless communication technology known as Reconfigurable Intelligent Surfaces (RIS). RIS consists of flat surfaces with programmable elements that manipulate electromagnetic waves, including high-frequency signals used in wireless communications.

When RIS sheets are placed on walls and ceilings, they can intercept and intelligently redirect wireless signals from outside to improve performance. As RIS technology evolves and integrates with existing 5G and future 6G networks, it promises to address the limitations of current indoor positioning technologies like GPS.

Professor Qammer Abbasi, from the University of Glasgow’s James Watt School of Engineering and the corresponding author of the paper, explained, “While GPS is highly effective outdoors, it struggles indoors due to signal weakening by thick walls and interference from other electronic signals. RIS can enhance indoor location-finding by precisely tracking the communications signals sent and received by devices like mobile phones.”

This technology can focus signals directly to mobile phone antennas, significantly improving call quality regardless of the user’s indoor location. The research represents a crucial step forward in refining RIS technology for indoor localization within future communication networks.

To explore the location-finding potential of RIS, the team set up a 1.3m-square RIS with 4,096 elements at the University of Glasgow. They paired it with two universal serial radio peripherals, one acting as a transmitter and the other as a receiver. During the first phase of the experiment, the researchers adjusted the RIS to effectively reflect signals from the transmitter to the receiver by steering the beam between nine positions and sending test signals at each location. In the second phase, they used various machine learning algorithms to analyze the unique “fingerprints” of the RIS-optimized signals at each position, determining which algorithm most accurately pinpointed the receiver’s location. One algorithm stood out, achieving an accuracy rate of 82.4%.

Dr. Syed Tariq Shah, the paper’s first author, who conducted the research at the University of Glasgow before joining the University of Essex, commented, “Our research demonstrates the potential of RIS to shape and direct wireless signals in innovative ways. This technology could manage crowds at large events or enable better tracking of stock in warehouses.”

Professor Muhammad Imran, leader of the University of Glasgow’s Communications, Sensing, and Imaging Hub and a co-author of the paper, noted, “This work marks a significant milestone in solving complex indoor localization problems. It will be one of the added benefits of 6G networks in the future.”

The research was funded by various sources, including the European Horizon 2020 Research and Innovation Programme, the Swedish Research Council, and the Swedish Foundation for Strategic Research. Additional support came from the eSSENCE Research Programme, AI4Research at Uppsala University, the Margaretha af Ugglas Foundation, and the National Academic Infrastructure for Supercomputing in Sweden at UPPMAX.

By Impact Lab