DocumentCode :
3472167
Title :
On low complexity cooperative spectrum sensing for cognitive networks
Author :
Xiong, Gang ; Kishore, Shalinee ; Yener, Aylin
Author_Institution :
Dept. of Electr. & Comput. Eng., Lehigh Univ., Bethlehem, PA, USA
fYear :
2009
fDate :
13-16 Dec. 2009
Firstpage :
145
Lastpage :
148
Abstract :
This paper presents a practical system design approach for cooperative spectrum sensing in cognitive sensor networks. An optimization problem is formulated, where the objective is to choose appropriate number of samples used in local energy calculation and linear combination weights for a global fusion center that together maximize global spectrum detection probability. Depending on the local information available to the fusion center and secondary users, practical system design is proposed in high fusion signal to noise ratio (SNR) regime, which has minimal implementation complexity and negligible performance loss, thus provides an efficient system design alternative in practice. Simulation results are presented to verify the analytical results.
Keywords :
cognitive radio; computational complexity; optimisation; sensor fusion; signal detection; SNR; cognitive networks; cooperative spectrum sensing; global fusion center; global spectrum detection probability; linear combination weights; local energy calculation; optimization problem; signal to noise ratio; Analytical models; Computer networks; Conferences; Performance loss; Probability; Sensor systems; Signal to noise ratio; Statistical analysis; System analysis and design; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2009 3rd IEEE International Workshop on
Conference_Location :
Aruba, Dutch Antilles
Print_ISBN :
978-1-4244-5179-1
Electronic_ISBN :
978-1-4244-5180-7
Type :
conf
DOI :
10.1109/CAMSAP.2009.5413316
Filename :
5413316
Link To Document :
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