Current Research Projects
Some of the current research projects being pursued are as follows:
Cross Layer Design for Wireless Communications
The project essentially deals with studying the trade-offs between multiple antennas/antenna arrays systems at the physical layer (PHY) in terms of signal to interference plus noise ratio (SINR), designing a scheduler that uses PHY information such as channel conditions and direction of arrival (DoA) to make the scheduling decision, studying the performance of the scheduler in terms of SINR under various fading conditions and in the presence of various users, performing capacity analysis of the proposed scheduler, simulating quality of service in terms of SINR and delay for the proposed scheduler and two of its modifications, and comparing these schedulers with other schedulers in terms of maximum delay and minimum SINR threshold violations.
For more information contact Deepali Arora
DSP Techniques for the Analysis of Genomic and Proteomic Signals
The project involves using various digital signal processing tools to develop new and efficient techniques of analyzing and annotating different kinds of genomic and proteomic signals, such as raw DNA sequences, protein sequences, and DNA microarrays. So far, two new techniques of locating hot spots in proteins have been developed and successfully tested. Currently, attempts to improve these techniques in terms of the accuracy of hot-spot locations are being made. The development of new techniques for analyzing DNA sequences and microarrays is also being explored.
For more information contact Parameswaran Ramachandran
Multiframe Image Super-Resolution
The availability of high-quality, high-resolution images is critical in several applications like medical diagnosis, remote sensing and surveillance to name a few. One promising approach towards improving the quality and spatial resolution capabilities of current imaging systems is by using signal processing-based techniques known as super-resolution. The research carried out in this project seeks to improve the efficiency of a particular class of super-resolution algorithms by applying sophisticated optimization methods. An algorithm based on a reformulation of a quasi-Newton optimization method and a powerful super-resolution approach has been developed and shown to achieve higher quality images.
For more information contact Diego Ariel Sorrentino
ICI Reduction in OFDM Systems
Orthogonal frequency-division multiplexing (OFDM) modulation is widely used in communication systems to meet the demand for ever-increasing data rates. However, it is sensitive to Doppler spread caused by user mobility, which results in a loss of orthogonality among subcarriers, and in turn leads to intercarrier interference (ICI). We seek an appropriate optimization framework for the formulation and solution of the ICI reduction problem.
For more information contact Yihai Zhang
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