Long-Distance Wi-Fi
Protocol extends the range of wireless networks
Results: Researchers in India have developed a communications protocol to increase the coverage area of Wi-Fi mesh networks. In a conventional Wi-Fi network – like the ones that are now common at many urban cafEs and airports – a base station with a wired connection to the Internet exchanges radio signals with users’ portable devices.
In a Wi-Fi mesh network, by contrast, several nodes can exchange radio signals with each other as well as with users. Such a network can provide Wi-Fi coverage for a given geographical area at a lower cost than a series of conventional Wi-Fi networks, because not all of its nodes must be wired to the Internet.
The new protocol enables off-the-shelf Wi-Fi radios to form mesh networks with distances of up to 40 kilometers between their nodes – compared with one kilometer or less for existing Wi-Fi mesh networks – while maintaining or even increasing data transfer speeds.
In a simulation of a mesh network with nodes at least seven kilometers apart, the researchers achieved data transmission speeds 20 times as high as those possible with Wi-Fi’s existing protocol.
Why It Matters: Wi-Fi networks are cheap and easy to set up, but their transmitters have a range of only about 100 meters. Meshed Wi-Fi networks can cover large urban and rural areas, but they don’t solve the problem of Wi-Fi’s inherently short range. Current Wi-Fi mesh networks typically require several nodes per square kilometer. Having fewer nodes spaced farther apart can result in lower data speeds and reliability.
Because the new communications protocol, developed by Bhaskaran Raman and Kameswari Chebrolu of the Indian Institute of Technology in Kanpur, increases the range of Wi-Fi while maintaining high data speeds or even increasing them, it may reduce the number of nodes needed and hence the cost of blanketing a large area with wireless Internet access, all without sacrificing performance.
Other technologies, including more-powerful antennas, have been developed to increase the range of Wi-Fi transmitters, but they work for only two nodes at a time; the new protocol enables multiple nodes to communicate with each other over long distances, while reducing interference and thus maximizing data speeds.
Methods: Every wireless network must have a communications protocol called a medium access control (MAC), which coOrdinates which radios can send signals when, so that they all transmit in an orderly fashion. In a mesh network, a node consists of multiple radios, each transmitting independently on a separate link to another node. The current MAC for Wi-Fi mesh networks allows some radios in a node to transmit signals at the same time that other radios are receiving signals, leading to interference that can slow the rate of data transfer and cause other problems. The researchers’ MAC makes the radios in the same node either transmit only or receive only at any given time, avoiding interference and increasing data transmission speeds.
Next Step: The researchers plan to test their protocol in an outdoor deployment of a Wi-Fi mesh network covering 32 rural Indian villages. One intended application is two-way video to enable patients to “visit” doctors remotely. – By Corie Lok
Source: Raman, B., and K. Chebrolu. 2005. Design and evaluation of a new MAC protocol for long-distance 802.11 mesh networks. Presented at the Eleventh Annual International Conference on Mobile Computing and Networking. August 28-September 2. Cologne, Germany.
Gesture Recognizer
Computer interface understands gestures and speech
Results: Researchers from MIT have developed a computer interface that enables a user to manipulate virtual shapes projected onto a screen using gestures, such as pointing, and spoken commands, such as “make a red cube in the middle of the screen.” Standing in front of cameras mounted above the screen, a user can create a virtual cube, rotate it, and change its color and size. In one experiment, the researchers found that their gesture recognition system had an error rate of 6 to 17 percent with some gestures, but a zero error rate when the gesture was coupled with a corresponding spoken command.
Why It Matters: Using gestures and speech to control computers can be easier and more natural than using a keyboard and mouse. Commercial gesture interfaces, such as those that TV meteorologists use to interact with digital maps during newscasts, respond to hand or head movements in two dimensions and require the user to be a fixed distance from the camera.
Other systems recognize full-body movements, but typically require users to wear markers or special garments, which can be cumbersome. This system, designed by David Demirdjian and colleagues, recognizes head, torso, and arm movements in three dimensions. Users don’t need to wear markers, and the system responds in real time. By combining gesture and voice inputs, the system more accurately follows different commands.
Methods: The software runs on a PC connected to three cameras and a microphone array. The researchers asked 10 subjects to perform 50 gestures in front of the cameras. Half of this data was used to “train” the software to recognize specific gestures. The software works by first estimating the user’s body position based on the camera images and then putting together sequences of poses to identify gestures. The researchers incorporated an existing speech recognition system into their setup. They used the other half of the gesture data from the performing subjects to test the overall accuracy of their system.
Next Step: The researchers would like to improve their software so that it recognizes more-natural gestures and handles conversational interactions. They would also like their system to be able to recognize gestures from multiple users at the same time. – By Corie Lok
Source: Demirdjian, D., T. Ko, and T. Darrell. 2005. Untethered gesture acquisition and recognition for virtual world manipulation. Virtual Reality. In press.