DocumentCode
3526454
Title
Optimal linear fusion for distributed spectrum sensing via semidefinite programming
Author
Quan, Zhi ; Ma, Wing-Kin ; Cui, Shuguang ; Sayed, Ali H.
Author_Institution
Dept. of Electr. Eng., Univ. of California, Los Angeles, CA
fYear
2009
fDate
19-24 April 2009
Firstpage
3629
Lastpage
3632
Abstract
As an enabling functionality of overlay cognitive radio networks, spectrum sensing needs to reliably detect licensed signal in the band of interest. To achieve reliable sensing, we propose a linear fusion scheme for distributed spectrum sensing to combine the sensing results from multiple spatially distributed cognitive radios. The optimal linear fusion design is formulated into a nonconvex optimization problem. We show that the optimal solution of such a nonconvex problem can be solved via semi-definite programming reformulation.
Keywords
cognitive radio; concave programming; sensor fusion; signal detection; distributed spectrum sensing; nonconvex optimization; optimal linear fusion scheme; overlay cognitive radio network; semidefinite programming; signal detection; Chromium; Cognitive radio; Computer network reliability; Design optimization; FCC; Functional programming; Iterative algorithms; Light rail systems; Linear programming; Signal detection; Spectrum sensing; cognitive radio; distributed detection; nonconvex optimization; semi-definite programming;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech and Signal Processing, 2009. ICASSP 2009. IEEE International Conference on
Conference_Location
Taipei
ISSN
1520-6149
Print_ISBN
978-1-4244-2353-8
Electronic_ISBN
1520-6149
Type
conf
DOI
10.1109/ICASSP.2009.4960412
Filename
4960412
Link To Document