Distributed cognitive spectrum sensing via group sparse total least-squares

Emiliano Dall'Anese, Georgios B. Giannakis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

Dynamic re-use of licensed bands under the hierarchical spectrum access paradigm calls for innovative network-level sensing algorithms for spectrum opportunity awareness in the frequency, time, and space dimensions. Toward this direction, the present paper develops a distributed spectrum sensing algorithm whereby cognitive radios (CRs) cooperate to localize active primary user (PU) transmitters, and estimate their transmit-power spectral densities. The sensing scheme relies on a parsimonious linear system model that accounts for two forms of sparsity: one due to the narrow-band nature of PU transmissions compared to the large swath of monitored frequencies; and another one emerging when employing a spatial grid of candidate PU locations. Capitalizing on this dual sparsity, and combining the merits of Lasso, group Lasso, and total least-squares (TLS), a group sparse (GS) TLS problem is formulated to obtain hierarchically-sparse model estimates, and cope with model uncertainty induced by channel randomness, and grid-induced model offsets. The GS-TLS problem is collaboratively solved by the CRs in a distributed fashion, using only local message exchanges among neighboring nodes. In spite of the non-convexity of the GS-TLS criterion, the novel distributed algorithm has guaranteed convergence to (at least) a locally optimal solution. The analytical findings are corroborated by numerical tests.

Original languageEnglish (US)
Title of host publication2011 4th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2011
Pages341-344
Number of pages4
DOIs
StatePublished - 2011
Event2011 4th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2011 - San Juan, Puerto Rico
Duration: Dec 13 2011Dec 16 2011

Publication series

Name2011 4th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2011

Other

Other2011 4th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2011
CountryPuerto Rico
CitySan Juan
Period12/13/1112/16/11

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