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© Newswise.
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New Tools to Predict, Help Avoid Wireless Signal Fades
NC State University News Services NEWS RELEASE Media Contacts: Jan. 18, 2001 Studies Yield New Tools to Predict, Help Avoid Wireless Signal Fades FOR IMMEDIATE RELEASE Nearly all mobile phone users experience problems with signal fade-ins, fade-outs and break-ups. The same problems can wreak havoc on wireless transmissions of high-speed digital, video or multimedia data. Until now, most scientists believed that the signal fading that causes such interruptions was random, unpredictable and largely unavoidable. But in a series of pioneering studies, researchers at North Carolina State University have shown otherwise. They've found that wireless signal fluctuations can be tracked and predicted far ahead of when they occur. The researchers have developed a forecast technology -- technically, an adaptive long-range channel-fading prediction algorithm -- that can accurately predict several milliseconds in advance when wireless signals will fade or fluctuate. "Several milliseconds may not sound like much advance notice, but it's the equivalent of hundreds of digital bits in a wireless transmission," said Dr. Alexandra Duel-Hallen, associate professor of electrical and computer engineering at NC State. "That's enough time to allow a transmitter to switch to other frequencies or antennas that may have stronger signals to the wireless receiver," she said. "If switching frequencies or antennas isn't possible or practical, the transmitter and receiver would still have enough time to agree to vary the rate of data transmission to minimize the interference," said Dr. Hans Hallen, assistant professor of physics at NC State. "They can exchange the data at very high bit rates when a channel is predicted to be strong, or to slow down the transmission to reduce errors when weak signaling is predicted," Hallen explained. The husband-and-wife team's research is supported by National Science Foundation grants, the Center for Advanced Computing and Communications grants, and by NC State's College of Engineering and College of Physical and Mathematical Sciences. A former student, Dr. Shengquan Hu, now at Philips Semiconductor Inc. in San Jose, Calif., and Ph.D. student Tugay Eyecoz, employed by Nortel Networks in Dallas, Texas, have contributed to the studies. The strength of a wireless signal can be weakened by many things. These fall into two groups: those that create signal variations over long distances, such as shadowing by buildings or terrain; and those that create strong and abrupt variations in which the signal intensity can change by up to a hundred-fold over distances of less than a foot. It is this type of signal variation -- caused by the overlap of signals reflected from buildings, vehicles, signs and other physical obstacles -- that the NC State research team studies and tracks. When you walk or drive as you use your mobile phone, these reflections and their overlap changes. The algorithm devised by Duel-Hallen, Hallen and their team not only takes these factors into account, but also accommodates for problems created by high vehicle speeds and high transmission frequencies. "In the future, as wireless goes to higher and higher frequencies, this long-range prediction will be essential for efficient adaptation of the transmitted signal to channel conditions due to the much faster channel intensity variations," Duel-Hallen said. To confirm their algorithm's accuracy, Hallen devised a realistic physical model, and the team tested it against narrowband measurements of real-life wireless signalling from suburban traffic in Stockholm, Sweden. The data was provided to NC State by Drs. Jan-Eric Berg and Henrik Asplund of Ericsson Radio Systems AB. Devising the new model was necessary, Hallen says, because no existing models provided insights into the rapid signal-level variations the team was tracking. "The existing models didn't take into account real-world situations such as the physical movement of phones relative to buildings and terrain, and other factors that can change in a second," he said. Both the forecast algorithm and the realistic physical model technologies are still in the research stages. However, the NC State researchers are talking with scientists at several companies that may further develop the technology for use in commercial wireless phones. -- lucas -- Editor's note: Following is an abstract from a technical paper published last year: Long Range Prediction of Fading Signals: Enabling Adaptive Transmission for Mobile Radio Channels ABSTRACT: Recently it was proposed to adapt several transmission methods, including modulation, power control, channel coding and antenna diversity to rapidly time variant fading channel conditions. Prediction of the channel coefficients several tens-to-hundreds of symbols ahead is essential to realize these methods in practice. We describe a novel adaptive long range fading channel prediction algorithm (LRP) and its utilization with adaptive transmission methods. This channel prediction algorithm computes the linear Minimum Mean Squared Error (MMSE) estimates of future fading coefficients based on past observations. This algorithm can forecast fading signals far into the future due to its significant memory span, achieved by using a sufficiently low sampling rate for a given fixed filter size. The LRP is validated for standard stationary fading models, and tested with measured data and with data produced by our novel realistic physical channel model. This model accounts for the variation of the amplitude, frequency and phase of each reflected component of the fading signal. Both numerical and simulation results show that long range prediction makes adaptive transmission techniques feasible for mobile radio channels.
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