Paper Info
Title
A Novel Multiple Antennas Based Centralized Spectrum Sensing Technique.
Abstract
In wireless communication, sensing failure, reliability, and fading affects the radio signals. Adaptive threshold and multiple antennas are one of the solutions of such problems. In this paper, authors introduced a novel multiple antennas based centralized spectrum sensing SS technique for cognitive radio networks CRNs. This paper is divided into two parts: part A uses multiple antennas based improved sensing detector MA_ISD, and part B uses multiple antennas based centralized spectrum sensing MA_CSS technique. Now, in the part A: the presented scheme uses two detectors TD concept, first one is an energy detector with a single adaptive threshold ED-SAT and the second one is an energy detector with two adaptive thresholds ED-TAT. Both detectors imply multiple antennas, following selection combination to select best signals. The proposed model enhances the detection performance and takes less sensing or detection time. The thresholds are adaptive as they are dependent on noise variance $$ \\sigma_{\\omega }^{2} $$, and the value of this noise variance changes according to the noise signal. Both the detectors work simultaneously and their output is then fed to a decision device which takes the decision using an OR rule. Results confirm that the presented multiple antennas based improved sensing detector MA_ISD technique improves the detection performance by 24.6%, 53.4%, 37.9%, and 49.6%, as compared to existing schemes i.e. EDT-ASS-2015 scheme, ED and cyclo-2010, adaptive SS-2012, and conventional-ED scheme at -12﾿dB signal-to-noise ratio SNR, respectively, while the number of antennas Nr﾿=﾿2. Meanwhile, proposed technique also decreases sensing time in the order of 47.0﾿ms, 49.0﾿ms, and 53.2﾿ms as compared to existing schemes EDT-ASS-2015, Adaptive SS-2012, and ED and Cyclo-2010 scheme at -20﾿dB SNR respectively. Further, in the part B: cooperative SS CSS is introduced in which the local decisions from each cognitive radio are transferred to a fusion center FC that decides the final decision and shares the decision to every cognitive radio. It is also found that the proposed detection technique with CSS when a number of cognitive radio CR users k﾿=﾿10, and Nr﾿=﾿2, achieves detection performance as per IEEE 802.22 at very low SNR i.e. -20﾿dB.
Year
DOI
Venue
2017
10.1007/978-3-662-54563-8_4
Trans. Computational Science
Field
DocType
Volume
Telecommunications,Wireless,Noise (signal processing),Computer science,Fading,Electronic engineering,Fusion center,Sigma,Detector,Cognitive radio
Journal
29
Citations 
PageRank 
References 
2
0.82
11
Authors
3
Name
Order
Citations
PageRank
Jyotshana Kanti182.18
Geetam Singh Tomar2599.86
Ashish Bagwari3162.73