We consider decentralized multiantenna cognitive radio networks where the secondary (cognitive) users are granted simultaneous spectrum access along with the license-holding (prima...
Effective spectrum sensing is a critical prerequisite for multi-channel cognitive radio (CR) networks, where multiple spectrum bands are sensed to identify transmission opportuniti...
We propose a novel equalization method for doubly selective wireless channels, whose taps are represented by an arbitrary Basis Expansion Model (BEM). We view such a channel in the...
Tomasz Hrycak, Saptarshi Das, Gerald Matz, Hans G....
We present the Recursive Least Squares Dictionary Learning Algorithm, RLSDLA, which can be used for learning overcomplete dictionaries for sparse signal representation. Most Dicti...
We propose a variance-component probabilistic model for sparse signal reconstruction and model selection. The measurements follow an underdetermined linear model, where the unknown...