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Channel estimation
and equalization: Developed adaptive/iterative algorithm
for MIMO channel estimation and data detection. Algorithm
is able to cope with rapidly time-variant frequency-selective
channels by making a collective use of the structure underlying
the communication problem. Algorithm minimizes training
overhead and is able to perform recovery with no latency,
thus minimizing storage requirements and lending itself
to real-time applications. Various stages of the algorithm
make use of dynamic programming and so can be efficiently
implemented using dedicated hardware. The algorithm was
applied in the wireless LAN context.
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Performance analysis
of adaptive algorithms: Performed a unified analysis
of a large class of adaptive
algorithms. Analysis unifies and extends earlier analysis
approaches; is able to predict stability and learning behavior
of many adaptive algorithms very accurately. It allows the
user to choose the adaptive algorithm best suited for a
given application; applies regardless of type of nonlinearity
employed in the algorithm and irrespective of the color
or statistics of data driving the adaptive algorithm.
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