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 :
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