The study aimed to improve the performance of an emerging wireless communication technology called Reconfigurable Intelligent Surfaces (RIS).
According to the researchers, this advancement in RIS technology could have a wide range of applications, from helping emergency services find people trapped in smoke-filled buildings, to offering device-assisted navigation through public spaces for blind and partially-sighted people.
It could also help eliminate the need to move around indoors to find the best position to make a mobile phone call.
RIS takes the form of flat surfaces which use programmable elements capable of manipulating electromagnetic waves, like the high-frequency signals of wireless communications, for a range of applications.
Sheets of RIS placed on walls and ceilings indoors can intercept wireless signals from outside and intelligently reflect, redirect and focus them as required to improve performance.
As RIS development progresses and the technology is integrated into existing 5G and future 6G communications networks, it could help solve a longstanding problem with the performance of more established positioning technologies like GPS.
In a statement, Professor Qammer Abbasi, of the University of Glasgow’s James Watt School of Engineering and lead researcher, said: “While GPS works very well outdoors, helping us to use mapping apps to find our way efficiently on foot or in a vehicle, it works considerably less well in indoor environments. Positioning communication signals can be weakened by thick walls or interfered with by other electronic signals, reducing the accuracy of GPS.
“RIS has the potential to greatly improve active location-finding indoors. It can do that by being aware of the communications signals being sent and received from devices like mobile phones at any given time, which allows them to precisely locate the device and its user.”
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To develop the technology’s location-finding potential, the research team, with colleagues from the UK and America, set up a 1.3m-square RIS containing 4,096 elements in a space at the University of Glasgow. They paired it with two devices called universal serial radio peripherals – one acted as a receiver of wireless signals and the other as a transmitter.
In the first phase of the experiment, the researchers configured the RIS’ ability to reflect signals from the transmitter to the receiver effectively by steering the beam between nine different positions and sending test signals at each location.
In the second phase, the team used a series of different machine learning algorithms to analyse the unique ‘fingerprints’ of the RIS-optimised wireless signals at each location, testing which algorithm could pinpoint the signals most accurately.
One algorithm clearly outperformed the others, proving itself capable of accurately determining the location of the receiver 82.4 per cent of the time.
Dr Syed Tariq Shah, first author of the paper, said: “This research shows that RIS can be used to shape and direct wireless signals in ways that have a lot of exciting future applications once RIS devices evolve and become more widely adopted across communications networks.
“The system we’ve prototyped could help with to develop improved management of crowds of people carrying mobile phones at large public events, or enable warehouse managers to keep better track of stock tagged with wireless transmitters. It could be applied to any situation where active positioning of signals from wireless devices is required.”
The research, published in Communications Engineering, can be read in full here.
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