Probability of detection and probability of false alarm in cooperative spectrum sensing for cognitive radio systems using hard fusion rules

2021 ◽  
Author(s):  
V. Aswini ◽  
A. Vamshidhar Reddy ◽  
Ch. Narendar ◽  
N. Renuka
Keyword(s):  
Cognitive Radio ◽  
False Alarm ◽  
Spectrum Sensing ◽  
Cooperative Spectrum Sensing ◽  
Probability Of Detection ◽  
Fusion Rules ◽  
Probability Of False Alarm ◽  
Cognitive Radio Systems ◽  
Radio Systems

scholarly journals Spectrum Sensing in Cognitive Radio

2012 ◽  
pp. 29-42
Author(s):  
Wei-Ho Chung
Keyword(s):  
Cognitive Radio ◽  
False Alarm ◽  
Fading Channels ◽  
Spectrum Sensing ◽  
Cognitive Radios ◽  
Probability Of Detection ◽  
Sensor Nodes ◽  
Fusion Rules ◽  
Probability Of False Alarm ◽  
Individual Decisions

The cognitive radio has been widely investigated to support modern wireless applications. To exploit the spectrum vacancies in cognitive radios, the chapter considers the collaborative spectrum sensing by multiple sensor nodes in the likelihood ratio test (LRT) frameworks. In this chapter, the functions of sensors can be served through the cooperative regular nodes in the cognitive radio, or the specifically deployed sensor nodes for spectrum sensing. In the LRT, the sensors make individual decisions. These individual decisions are then transmitted to the fusion center to make the final decision, which provides better detection accuracy than the individual sensor decisions. The author provides the lowered-bounded probability of detection (LBPD) criterion as an alternative criterion to the conventional Neyman-Pearson (NP) criterion. In the LBPD criterion, the detector pursues the minimization of the probability of false alarm while maintaining the probability of detection above the pre-defined value. In cognitive radios, the LBPD criterion limits the probabilities of channel conflicts to the primary users. Under the NP and LBPD criteria, the chapter provides explicit algorithms to solve the LRT fusion rules, the probability of false alarm, and the probability of detection for the fusion center. The fusion rules generated by the algorithms are optimal under the specified criteria. In the spectrum sensing, the fading channels influence the detection accuracies. The chapter investigates the single-sensor detection and collaborative detections of multiple sensors under various fading channels and derives testing statistics of the LRT with known fading statistics.

An Algorithm Based on Double-Threshold Energy Detection in Cognitive Radio

2014 ◽  
Vol 643 ◽  
pp. 105-110
Author(s):  
Yuan Li ◽  
Jia Yin Chen ◽  
Xiao Feng Liu ◽  
Ming Chuan Yang
Keyword(s):  
Cognitive Radio ◽  
False Alarm ◽  
Spectrum Sensing ◽  
Mathematical Proof ◽  
Threshold Energy ◽  
Energy Detection ◽  
Probability Of Detection ◽  
Threshold Detection ◽  
Probability Of False Alarm ◽  
Double Threshold

Aiming at the situation where the double-threshold detection has been widely used without complete mathematical proof and condition of application, this paper proves its correctness under the circumstance of spectrum sensing, and circulates the condition where this method can work. The proof and simulation show that, comparing with traditional energy detection, this method can increase the probability of detection by 27% to 42% at most when the SNR is between-15dB and-2dB, while the probability of false alarm is increased by less than 2%.

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