Paper Info
Title
Improving Spectrum Sensing and Reporting via Multi-Antenna in Cognitive Radio Networks
Abstract
Spectrum sensing is a vital functionality of cognitive radio network to identify an available spectrum for secondary users to enhance spectrum utilization and to avoid harmful interference to licensed users. However, the performance of spectrum sensing is highly degraded due to fading and hidden terminal issues. Recent development in multiantenna techniques provides a new dimension to spectrum sensing. In this paper, we propose a multi-antenna based signal detection scheme in multi-band systems. We consider an ordered sequential data fusion scheme i.e., Dempster-Shafer (D-S) evidence theory, which increases system reliability. Also, an ordered sequential reporting mechanism is proposed for multiantenna based systems to enhance the system performance by reducing reporting time duration. The effectiveness of the proposed scheme is demonstrated through simulations, compared with existing schemes.
Year
DOI
Venue
2019
10.1109/ICUFN.2019.8806146
2019 Eleventh International Conference on Ubiquitous and Future Networks (ICUFN)
Keywords
Field
DocType
Cognitive radio,data fusion center,Dempster-Shafer(D-S) theory,multi-antenna,multi-band,ordered sequential reporting
Sequential data,Multi band,Detection theory,Fading,Computer science,Real-time computing,Interference (wave propagation),Fusion scheme,Distributed computing,Cognitive radio,Data fusion center
Conference
ISSN
ISBN
Citations 
2165-8528
978-1-7281-1341-8
0
PageRank 
References 
Authors
0.34
7
5
Name
Order
Citations
PageRank
Muhammad Sajjad Khan132.76
Mi Ji Kim200.68
Junsu Kim353.46
Eung Hyuk Lee432.44
Su Min Kim512919.92