In a pair of papers appearing in October in the journal IEEE Transactions on Information Theory, MIT researchers present a new theory that establishes fundamental limits on the accuracy of wireless location detection. By demonstrating which aspects of wireless signals convey the most reliable location information, the work points the way toward better location-detection algorithms.In the last 10 years, the possibility of using wireless connections to deduce mobile devices? locations has been a hot research topic in industry and academia. GPS systems frequently fail in large buildings, and even when they don‘t, they’re not very precise. Firefighters tracking each other in a smoke-filled building, soldiers trying to determine each other’s position in urban environments, medical staff trying to locate equipment or each other in a busy hospital, and warehouse workers trying to find merchandise in an aisle of pallets stacked 20 feet high all need higher-resolution location information than GPS can provide.Heavy hitters like Google, Intel and Nokia have all experimented with wireless localization, but MIT’s Wireless Communications and Network Sciences Group in the Laboratory for Information and Decision Systems (LIDS) is taking a more fundamental approach to the problem.In the new papers, Moe Win, a professor in the Department of Aeronautics and Astronautics who heads the group, graduate student Yuan Shen, and former postdoc Henk Wymeersch analyze networks in which wireless devices are working together to determine their locations. The researchers derive fundamental limits on the accuracy of the networks? location information, even in harsh environments in which signals are bouncing off of obstacles and interfering with each other.Among their insights is that networks of wireless devices can improve the precision of their location estimates if they share information about their imprecision. Traditionally, a device broadcasting information about its location would simply offer up its best guess. But if, instead, it sent a probability distribution - a range of possible positions and their likelihood - the entire network would perform better as a whole. The problem is that sending the probability distribution requires more power and causes more interference than simply sending a guess, so it degrades the network‘s performance. Win’s group is currently working to understand the trade-off between broadcasting full-blown distributions and broadcasting sparser information about distributions. Wireless positioning systems can use a variety of strategies, Win explains. They might measure the received power of the signal; they might measure the time elapsed between the emission of a signal and its reception; or they might measure the angle at which the signal arrives. By quantifying the accuracy of the information provided by each of these approaches, Win’s group is explaining which should be practically exploited and how. ‘Everything that we do, we try to approach in three steps,’ Win says. ’One is to try to understand ultimate limits: We just want to know, ’What’s the best we can do?? The second thing that we try to do is to design practical algorithms that approach these limits.’ If mathematical analysis and computer simulations suggest that an algorithm is promising, Win says, ‘The third aspect is experimental verification.’In order to collect data reliable enough to underwrite such fine-grained theoretical analysis, Wesley Gifford, who just received his PhD as a member of Win’s group, developed a robotic system that can position a wireless transmitter with millimeter accuracy on a surface about the size of a Ping Pong table. Win’s group has used the apparatus across the MIT campus to characterize extremely wideband wireless channels.Source: - Fundamental Limits of Wideband Localization - Part I: A General Framework ,? by Moe Z. Win and Yuan Shen. IEEE Transactions on Information Theory; - Fundamental Limits of Wideband Localization - Part II: Cooperative Networks ,? by Henk Wymeersch, Moe Z. Win, Yuan Shen. IEEE Transactions on Information Theory.
Funding: National Science Foundation, Office of Naval Research, MIT Institute for Soldier Nanotechnologies