Cities are encountering extensive deficits in infrastructure service while they are
experiencing rapid technological advancements and overhauls in transportation systems …

Spatiotemporal signal reconstruction from samples randomly gathered in a multidimensional
space with uncertainty is a crucial problem for a variety of applications. Such a problem …

Analytical methods for finding moments of random Vandermonde matrices with entries on
the unit circle are developed. Vandermonde matrices play an important role in signal …

We use the theory and algorithms developed for so-called shift-invariant spaces to develop
a novel distributed architecture for sampling and reconstructing time-varying non …

Phase reconstruction is in general a non-trivial problem when it comes to devices where the
reference is not accessible. A non-convex iterative optimization algorithm is proposed in this …

We develop a new class of event detection algorithms in Wireless Sensor Networks where
the sensors are randomly deployed spatially. We formulate the detection problem as a …

This paper addresses pilot-assisted channel estimation for wireless orthogonal frequency
division multiplexing (OFDM) systems with irregular pilot arrangements. Using nonuniform …

In remote sensing with a large array of spatially distributed sensors, localization of individual
sensor nodes could be difficult. Motivated by the smart-dust paradigm, this work addresses …

Sampling of physical fields with mobile sensor is an emerging area. In this context, this work
introduces and addresses some aspects of a fundamental question: can a spatial field be …

The dramatic increase in the number and sensing capabilities of mobile devices is fostering
opportunistic sensing as a paramount data collection paradigm in smart cities. According to …