DocumentCode
593595
Title
Beamforming with efficient node selection techniques for green cognitive radio networks
Author
Tessema, N.M. ; Lian, Xiang ; Nikookar, Homayoun
Author_Institution
Fac. of EEMCS, Delft Univ. of Technol., Delft, Netherlands
fYear
2012
fDate
Oct. 31 2012-Nov. 2 2012
Firstpage
626
Lastpage
629
Abstract
Distributed Beamforming conserves power consumption of wireless sensor networks and extends communication range by focusing the transmit signal energy in the direction of the receiver. Significant saving of power consumption is obtained by only selecting the optimal number of nodes prior to beam forming which are necessary to form the communication link. A new node selection method based on clustering is proposed. Clustering Method aims at minimizing interference on PU by selecting the combination of nodes with destructive carrier phase. Simulation results showed that the side lobe level was reduced down to -19.7 dB in the direction of primary users. This side lobe level would require N = 95 nodes to be involved in the beamforming process according to asymptotic side lobe relationship 10 log N1. Using clustering node selection method, it was possible to accomplish the same side lobe reduction in the direction of primary users using only 21 nodes.
Keywords
array signal processing; cognitive radio; interference suppression; radio receivers; wireless sensor networks; asymptotic side lobe relationship; clustering node selection method; communication range; distributed beamforming; green cognitive radio networks; interference suppression; side lobe reduction; transmit signal energy; wireless sensor networks; Array signal processing; Clustering methods; Interference; Receivers; Simulation; Wireless communication; Wireless sensor networks; Cognitive Radio(CR); Distributed beamforming(DB); Node Selection Techniques; Primary Users(PU);
fLanguage
English
Publisher
ieee
Conference_Titel
Radar Conference (EuRAD), 2012 9th European
Conference_Location
Amsterdam
Print_ISBN
978-1-4673-2471-7
Type
conf
Filename
6450713
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