AI is transforming healthcare by unlocking new possibilities for precision medicine, enabling doctors to tailor treatments to individual patients based on their unique characteristics, medical history, and genetic profile. AI algorithms can analyze vast amounts of patient data to identify patterns and correlations that may not be visible to human doctors, leading to earlier and more accurate diagnoses, as well as more targeted and effective treatments. AI-powered medical devices and wearable technology are also changing the way we monitor and manage our health, empowering patients to take a more active role in their care, resulting in a more personalized, effective, and accessible healthcare system.
Dr. Anas Chaaban, an Assistant Professor at UBC Okanagan’s School of Engineering, explained that the increasing use of mobile technologies across the world is necessitating research that unlocks potential new approaches within existing infrastructure. Even though cellphone towers line the rooftops of major cities and handle the data and phone traffic of millions of Canadians each day, there are still gaps in service. To address this, Dr. Chaaban and his team developed transmission schemes that would incorporate reconfigurable intelligent surfaces, or “smart surfaces,” throughout urban centers.
The researchers developed a new localization system where an RIS can work as a satellite to improve accuracy. By making a surface smart, it can bounce signals to cell phones, which in turn can use these signals to generate an accurate estimate of location. An accurate location estimate is not only useful for location services but also to improve transmission from the tower to the phone using optimized location-aware transmission schemes that also leverage the RIS.
Dr. Chaaban and his team tested their theory using multiple modulated RISs that allow for the simultaneous localization of multiple users with low complexity for each RIS. They also developed and tested RIS-enabled transmission schemes that outperform existing schemes, such as using multiple RISs to optimize coverage and capacity in a network.
The researchers simulated the proposed localization protocol and demonstrated its effectiveness in an urban micro-cell street canyon scenario, which is an example of a challenging environment for wireless networks. The protocol works for multiple users simultaneously, and even in areas with intermittent service, data can be shared, and users can be located to enjoy a reliable connection. This research could lead to more efficient use of existing infrastructure to improve wireless services, benefiting millions of Canadians who rely on their mobile devices for communication and navigation.
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