Research Interests:

As leader of the Advanced Signal Processing for Communications Research Group, Professor Wong works closely with other faculty members of the Group and is involved in several of the research projects. Specifically, Prof. Wong’s research interests are in the area of signal processing and communication theory. Current work being pursued include the following:

·               High Resolution Array Processing – An array of sensors can be placed strategically to collect data for the extraction of information. The application of sensor array processing in practice, however, encounters hostile environments far diverse from the ideal. Using advanced statistical methods, various high resolution techniques in array signal processing robust to the non-ideal environment are being developed here.

·               Adaptive Beamforming and Space-Time Signal Processing – Beamforming is the technique by which the radiation lobe of an antenna array is directed spatially at the desired signal while the null  of the array is steered to the interference. This enables the extraction of the desired signals and the suppression of the interfering signals using spatial separation of the two. Beamforming for moving sources is an important problem in mobile communication systems. Here, we develop adaptive signal processing algorithms utilizing both spatial and temporal information to facilitate the extraction of the desired signals efficiently in a time-varying environment.

·               Adaptive Filtering – Advanced optimization techniques for convex problems have been applied to develop adaptive filtering algorithms. Specifically, linear programming techniques have been applied to arrive at efficient blind adaptive fractionally spaced equalization. A highly efficient algorithm based on the interior point least squares approach has been developed having much faster convergence rate than the conventional recursive least squares approach. Further refinement and applications of the algorithm in communications are being considered.

·               Time-Frequency Analysis and Design of Signals – Applications of wavelets and other techniques in signal analysis and synthesis are being studied. The problems of adaptive filtering and signal compression are being investigated. The Wavelet Packet Division Multiplexing (WPDM) system, pioneered here at McMaster, continues to be a focus of research. Research on the optimum and robust designs of wavelets for WPDM are being carried out.

·               Multi-User Communication Systems – Advanced optimization techniques have been applied to arrived at optimum and sub-optimum designs of receivers in a multi-user communications environment. Extension to joint optimum designs of transmitters and receivers for multi-user communication systems is being pursued.

·               Biomedical Signal Classification – Innovative techniques in signal classification are being developed utilizing advanced mathematical concepts in signal space theory and differential geometry.  Initial results demonstrate that such an approach may yield dramatically improved accuracies.



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