Compressive Sampling of Pulse Trains : Spread the Spectrum !
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Consider classes of signals that have a finite number of degrees of freedom per unit of time and call this number the rate of innovation. Examples of signals with a finite rate of innovation include streams of Diracs (e.g., the Poisson process), nonuniform ...
Institute of Electrical and Electronics Engineers2002
We consider the problem of low-complexity channel estimation in digital ultra-wideband receivers. We extend some of our recent sampling results for certain classes of parametric non-bandlimited signals and develop several methods that take advantage of tra ...
We consider the problem of sampling signals which are not bandlimited, but still have a finite number of degrees of freedom per unit of time, such as, for example, piecewise polynomials. We demonstrate that by using an adequate sampling kernel and a sampli ...
Accuracy of oversampled analog-to-digital (A/D) conversion, the dependence of accuracy on the sampling interval, t, and on the bit rate are characteristics fundamental to A/D conversion but not completely understood. These characteristics are studied in th ...
Institute of Electrical and Electronics Engineers2001
We consider the problem of low-complexity timing synchronization in digital receivers for DS-CDMA and UWB systems operating over channels with single or multiple propagation paths. We extend some of our recent sampling results for certain classes of non-ba ...
Recently a sampling theorem for a certain class of signals with finite rate of innovation (which includes for example stream of Diracs) has been developed. In essence, such non band-limited signals can be sampled at or above the rate of innovation. In the ...
Sampling theory has prospered extensively in the last century. The elegant mathematics and the vast number of applications are the reasons for its popularity. The applications involved in this thesis are in signal processing and communications and call out ...
The field of signal processing has known tremendous progress with the
development of digital signal processing. The first foundation of digital signal processing is due to Shannon's sampling theorem which shows that any bandlimited analog signal can... ...
Many communication systems are {\em bandwidth-expanding}: the transmitted signal occupies a bandwidth larger than the {\em symbol rate}. The sampling theorems of Kotelnikov, Shannon, Nyquist et al. shows that in order to represent a bandlimited signal, it ...