Improving Wireless Location-Detection Systems

Researchers from the Massachusetts Institute of Technology are developing innovative techniques to improve existing methods used in location-detection systems. Unlike Global Positioning Systems (GPS), their project utilizes wireless devices in a whole new manner, offering potential applications new ways to communicate geographical data.
MIT researchers are developing a theoretical framework that could eventually be used to help pinpoint the location of mobile devices — represented here as blue dots — indoors, where GPS reception can be unreliable and inaccurate. (Credit: Christine Daniloff)
MIT researchers are developing a theoretical framework that could eventually be used to help pinpoint the location of mobile devices — represented here as blue dots — indoors, where GPS reception can be unreliable and inaccurate. (Credit: Christine Daniloff)

Many modern smartphone applications rely on geographical data. For instance, providing advertisements based on location (users receive invitation for a coffee from nearby cafés), or helping lost tourists to find their way back to their hotel requires such data. While commercial applications can tolerate the inaccuracy cellular-based or GPS-based systems have, some users – such as firefighters and soldiers – need more precise positioning capabilities. Moreover, it seems that existing technologies face trouble especially when used in buildings, making urban warfare (which relies on communicating positions) and medical applications less effective.

Now, the Wireless Communications and Network Sciences Group at the Massachusetts Institute of Technology (MIT) is working on a new approach towards the challenges positioning systems face. Using the instruments in the Laboratory for Information and Decision Systems (LIDS), they develop a theoretical framework that explains just how accurate wireless location information can be, depending on network characteristics like interference and available bandwidth. Hopefully, the results of their study will help create better algorithms.

The group’s leader is Moe Win, a professor in the Department of Aeronautics and Astronautics. He says the group’s work is divided into three phases. “One is to try to understand ultimate limits: We just want to know, ‘What’s the best we can do?’” he said. “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.”

Like in all academic studies, the three phases rely on empirical data. Even the mathematical model that underlies the rest of the group’s work is based on measurements of wireless signals in realistic environments. In order to collect data reliable enough to underwrite such fine-grained theoretical analysis, Wesley Gifford, one of the team members, developed a robotic system that can position a wireless transmitter with millimeter accuracy on a surface about the size of a Ping Pong table. The robot is built mostly from wood, since metal could interfere with the transmitter’s signal. The apparatus was used throughout the MIT campus, to characterize extremely wideband wireless channels.

The team published its results in the journal IEEE Transactions on Information Theory. The researchers analyzed networks in which wireless devices are working together to determine their locations, and their analysis focused on the fundamental limits; their motivation was finding the parameters affecting the accuracy of the networks’ location information. Specifically, they tested the networks in harsh environments, where signals were bouncing off obstacles and interfering with each other.

Several insights are provided in the paper; the major one is that networks of wireless devices can improve the precision of their location estimates if they share information about their imprecision. This is done by sending a probability distribution (a range of possible positions and their likelihood), instead of the common method, in which devices just send their best “guess.” The result of this new approach is general improvement for the entire network.

However, the problem with sending probability distribution is the requirement for more power – causing more interference than simply sending a guess; the result is reduced network performance. Therefore, Win’s group is working to understand the trade-off between broadcasting full-blown distributions and broadcasting sparser information about distributions.

According to Win, wireless positioning systems can use a variety of strategies; they might measure the received power of the signal, or they might measure the time elapsed between the emission of a signal and its reception. Another option is measuring the angle at which the signal arrives. By quantifying the accuracy of the information provided by each of these approaches, the team hopes it will be able to explain which one should be the most practical.

“The work exploits cooperation among low-cost wireless devices, rather than relying only on signals from fixed infrastructure, such as GPS systems,” said H. Vincent Poor, the dean of Princeton University’s School of Engineering and Applied Science. “The researchers have designed novel location-aware networks with sub-meter accuracy and high reliability.”

Poor points out that the researchers’ algorithms will probably require further development before they would be practical on larger networks, and the researchers are working on what Poor describes as “leaner” algorithms, so that they would not consume too much power in cheap wireless devices with limited battery life. While the research is not complete yet, he shows optimism: “I don’t see any major obstacles for transferring their basic research to practical applications. In fact, their research was motivated by the real-world need for high-accuracy location-awareness.”

TFOT also covered an innovative utilization of GPS, used for crowd management and medical treatment, and the AVENUE Urban Robot, designed to explore urban areas and create site models based on imaging and other collected data. Another related TFOT story is the MMC212xM, a magnetic sensor that will enable greatly improved location-based services in cellular phones and handheld GPS systems.

For more information about MIT’s efforts to improve wireless location-detection systems, see the official press release.

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