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Dr. Alexandra Duel-Hallen, ECE Department, NC State University

Dr. Alexandra Duel-Hallen and Dr. Hans Hallen have been awarded $267,384 by the Army Research Office for research on a Reconfigurable Outdoor Wireless Channel Measurement System.

The award will run from June 7th, 2009 to June 6th, 2010.

Research Abstract - Wireless communications systems are widely modeled and measured. The successful model by is used by many groups and forms the basis for understanding propagation effects in a standard wireless system. It only allows statistical description of a channel, however, so is not adequate for testing algorithms whose performance is strongly affected by the precise local environment. In particular, testing these algorithms requires the creation of scenarios that are typical and others that are challenging.

An example of such an algorithm is long-range prediction, which has been shown to enable adaptive modulation to achieve significant gains on the wireless channel, and is becoming widely studied. The variation of the channel parameters with position plays a large role in determining the achievable performance of the algorithm. We have developed a physical model to test long-range prediction. It provides the necessary insights for predicting challenging or typical scenarios, and creates simulated channels for testing long-range prediction that include physically realistic parameter variation in space. The physical model compares well with measurements for narrow band channels in a suburban environment, as judged by the performance of the long-range prediction algorithm. This is in contrast to the prediction of a Jake's model simulated channel, which does not include physically meaningful parameter variations (it is stationary).

As we modify the model to other situations, such as prediction at a frequency other than the one sampled, prediction near complex scattering objects, and peer-to-peer systems that utilize sectored antennas, we have moved well beyond comparison of the model to measured channels. The measurements needed to verify the model in these cases are too involved and need too much interaction with model building to be realistically carried out by a remote group. We therefore propose here to purchase equipment and develop the measurement capabilities to insure that the models are reasonable and to develop insights to further enhance the model for these and future projects.