Group Sparse Lasso for Cognitive Network Sensing Robust to Model Uncertainties and Outliers

To account for variations in the frequency, time, and space dimensions, dynamic re-use of licensed bands under the Cognitive Radio (CR) paradigm calls for innovative network-level sensing algorithms for multi-dimensional spectrum opportunity awareness. Toward this direction, the present paper develops a collaborative scheme whereby CRs cooperate to localize active Primary User (PU) transmitters and reconstruct a Power Spectral Density (PSD) map portraying the spatial distribution of power across the monitored area per frequency band and channel coherence interval. The sensing scheme is based on a parsimonious model that accounts for two forms of sparsity: one due to the narrow-band nature of transmit-PSDs compared to the large portion of spectrum that a CR can sense; and another one emerging when adopting a spatial grid of candidate PU locations.

Provided by: University of Minnesota Topic: Mobility Date Added: Apr 2011 Format: PDF

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