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Vincent Poor

My current research interests are in the area of statistical signal processing, primarily as applied to problems in wireless multiple-access communications. Research in this area supports the development of novel signal reception techniques for emerging wireless communication systems, such as wideband code-division multiple-access (W-CDMA) systems currently being standardized for voice and data (multimedia) applications. A principal challenge in the development of such systems stems from the physical properties of the communication channel, which can include impairments such as dispersion, fading, impulsive noise, cochannel/multiple-access interference, and narrowband interference, as well as phenomena such as spatial or path diversity in the form of multipath or multiple antennas at the transmitter and/or receiver. Further challenges include the dynamism that can arise in such channels due to mobility and to the use of random channel access protocols, the need for portability (and, hence, small size and low power consumption), and increasing demands for higher data rates and larger user populations. These challenges give rise to the need for new signal-processing algorithms to accomplish tasks such as channel equalization, multiuser detection and interference suppression, antenna beamforming, multipath combining, error-control decoding, and the mitigation of impulsive interference. Although methods for these tasks have been studied independently, a key to their successful application in environments such as that described above is to develop procedures for jointly accomplishing these tasks. Moreover, due to the dynamism of the channels, and to user security issues, many of these tasks must be performed adaptively and without full knowledge of all signal parameters. Our research has addressed these issues.

Recent progress includes the development and exploitation of signal-subspace techniques for blind adaptive implementation of joint multiuser detection and equalization, smart antenna techniques that incorporate joint spatial (that is, beamforming) and temporal (for example, multiuser detection) techniques, and iterative ("turbo") algorithms for joint multiuser detection and channel decoding. This research is described in several recent publications and disclosures that can be found listed at http://www.ee.princeton.edu/~steph/report97.html. Publications describing other very recent research progress in the areas of statistical change detection, and the statistical analysis of self-similar stochastic processes, can be found there as well.

Smart antenna system for multiple access communications