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. Wongs 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.