• 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.
• 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.