6 accepted papers
Many applications like audio and image processing show that sparse representations are a powerful and efficient signal modeling technique. Finding an optimal dictionary that generates at the same time the sparsest representations of data and the smallest approximation error is a hard problem approac…
In this paper, we propose a solution to the sensor management problem over multiple time instances that balances the accuracy of the sensor network estimation with its utilization. We show how this problem reduces to a binary optimization problem for which we give a convex relaxation based solution…
This paper addresses the problem of designing thinned arrays with minimized side lobe levels for antenna selection in millimeter wave MIMO systems. We propose a new optimization solution based on compressed sensing techniques and convex optimization relaxation which we show to be a heuristic that so…
In this paper we analyze the mean squared error (MSE) for one-bit compressed sensing schemes based on measurement matrices that correspond to unit norm tight frames. We show that, as in the unquantized case, sensing with unit norm tight frames improves the MSE in the reconstruction of sparse vectors…
Antenna subset modulation (ASM) is a physical layer security technique that is well suited for millimeter wave communication systems. The key idea is to vary the radiation pattern at the symbol rate by selecting one from a subset of patterns with a similar main lobe and different side lobes. This pa…
We propose a low complexity method for estimating direction of arrival (DOA) when the positions of the array sensors are affected by errors with known magnitude bound. This robust DOA method is based on solving an optimization problem whose solution is obtained in two stages. First, the problem is r…