In an increasingly connected world, the ability to accurately pinpoint the location of wireless devices is paramount. From enhancing navigation systems to improving emergency response, the applications are vast and vital. However, traditional localization methods often fall short, struggling with interference, obstacles, and varying environmental conditions. Our groundbreaking research in Wireless Localization seeks to overcome these challenges. By employing reconfigurable intelligent surfaces that manipulate electromagnetic waves, we aim to enhance the precision, reliability, and efficiency of wireless localization. This innovative approach not only addresses existing limitations but also opens new horizons for seamless connectivity and navigation, setting the stage for the next generation of wireless technology.
Reconfigurable Intelligent Surfaces
Reconfigurable Intelligent Surfaces (RIS) are redefining the boundaries of Wireless Localization, offering a solution that transcends traditional limitations. Comprising electronically controlled elements, RIS can shape and steer electromagnetic waves, even overcoming blocked paths that typically hinder conventional methods. This ability to navigate around obstacles and interferences is a game-changer, enhancing both precision and reliability. The motivation for employing RIS is rooted in its unparalleled adaptability, which provides a robust solution where other technologies falter. By actively manipulating the wireless landscape, RIS not only addresses existing challenges but also pioneers a new frontier in connectivity and navigation, setting a groundbreaking standard in the field.
Challenging Environments
Navigating near-field and multipath environments is a complex task that has long challenged the field of Wireless Localization. These environments, filled with reflections, scattering, and obstacles, can distort signals and block paths, leading to inaccuracies in localization. RIS offers a novel solution to these specific challenges. By shaping and steering electromagnetic waves, RIS can adeptly handle the intricacies of near-field complexity and multipath effects. This ability to adapt and overcome obstacles in challenging environments enhances localization accuracy and reliability, marking a significant stride forward in the pursuit of seamless connectivity and precise navigation.
LiDAR and RIS Synergy: A New Horizon in Wireless Localization Accuracy
Our research introduces a novel approach that combines the capabilities of RIS with light detection and ranging (LiDAR) technology. By utilizing LiDAR to gather geometric information about scatterers in the environment, we feed this data into a sparse recovery algorithm, reducing the variables to be estimated, such as angles of arrival and distances.
Enhanced Performance
Our innovative method, integrating LiDAR with reconfigurable intelligent surfaces (RISs), has redefined wireless localization performance. By synergizing LiDAR’s geometric insights with RIS’s adaptability, we’ve crafted a precise localization algorithm that navigates complex environments with ease. The result is a 65.57% boost in accuracy compared to traditional approaches, setting a new standard for efficiency and reliability in the field.
Selected Publications
- O. Rinchi, A. Elzanaty, and A. Alsharoa. “Single-Snapshot Localization for Near-Field RIS Model Using Atomic Norm Minimization.” in proc. of the IEEE Global Communication Conference (GLOBECOM), Rio de Janeiro, Brazil, Dec. 2022
- O. Rinchi, A. Elzanaty, and A. Alsharoa, “Wireless Localization with Reconfigurable Intelligent Surfaces”, 6G Wireless: The Communication Paradigm Beyond 2030, CRC Press, 2023.
- O. Rinchi, A. Elzanaty, and A. Alsharoa, “Enhancing Near-Field Wireless Localization with LiDAR-Assisted RIS in Multipath Environments”, IEEE Wireless Communications Letters, Aug. 2023.
Student Awards
- Omar Rinchi won 3rd place in the best research competition (oral session) of the Missouri S&T 2023 Graduate Research Showcase for his oral presentation titled “The Role of LiDAR Sensors in Future 6G Networks”.
- Omar Rinchi won 4th place in the Missouri S&T Council of Graduate Students (CGS) 2023 poster competition for his poster entitled “The Integration of LiDAR Sensors With Future 6G Wireless Networks”.
- Omar Rinchi won a special mention in the IEEE 2022 St. Louis Section student presentation competition for his research about RIS-aided localization.