The recently developed compressive sensing (CS) framework enables the design of sub-Nyquist analog-to-digital converters. Several architectures have been proposed for the acquisit...
John P. Slavinsky, Jason N. Laska, Mark A. Davenpo...
Due to multipath delay spread and relatively high sampling rate in OFDM systems, the channel estimation is formulated as a sparse recovery problem, where a hybrid compressed sensi...
We propose a compressive method for tracking doubly selective channels within multicarrier systems, including OFDM systems. Using the recently introduced concept of modified comp...
—Data loss in wireless communications greatly affects the reconstruction quality of a signal. In the case of images, data loss results in a reduction in quality of the received i...
Compressed sensing (CS) has recently emerged as a powerful signal acquisition paradigm. In essence, CS enables the recovery of high-dimensional sparse signals from relatively few ...
Jarvis Haupt, Waheed Uz Zaman Bajwa, Gil M. Raz, R...