Double Threshold-Based Energy Detection Spectrum Sensing Scheme by Considering the Sensing History in Confusion Region

2018 ◽  
Author(s):  
Smriti ◽  
Charan Chhagan
Keyword(s):  
Spectrum Sensing ◽  
Energy Detection ◽  
Double Threshold

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%.

scholarly journals Adaptive Double-Threshold Cooperative Spectrum Sensing Algorithm Based on History Energy Detection

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Shanshan Yu ◽  
Ju Liu ◽  
Jing Wang ◽  
Inam Ullah
Keyword(s):  
Spectrum Sensing ◽  
Cooperative Spectrum Sensing ◽  
Signal To Noise Ratio ◽  
Threshold Energy ◽  
Average Energy ◽  
Energy Detection ◽  
Detection Performance ◽  
Weighting Coefficient ◽  
Threshold Method ◽  
Double Threshold

Spectrum sensing is one of the key technologies in the field of cognitive radio, which has been widely studied. Among all the sensing methods, energy detection is the most popular because of its simplicity and no requirement of any prior knowledge of the signal. In the case of low signal-to-noise ratio (SNR), the traditional double-threshold energy detection method employs fixed thresholds and there is no detection result when the energy is between high and low thresholds, which leads to poor detection performance such as lower detection probability and longer spectrum sensing time. To address these problems, we proposed an adaptive double-threshold cooperative spectrum sensing algorithm based on history energy detection. In each sensing period, we calculate the weighting coefficient of thresholds according to the SNR of all cognitive nodes; thus, the upper and lower thresholds can be adjusted adaptively. Furthermore, in a single cognitive node, once the current energy is within the high and low thresholds, we utilize the average energy of history sensing times to rejudge. To ensure the real-time performance, if the average history energy is still between two thresholds, the single-threshold method will be used for the end decision. Finally, the fusion center aggregates the detection results of each node and obtains the final cooperative conclusion through “or” criteria. Theoretical analysis and simulation results show that the algorithm proposed in this paper improved detection performance significantly compared with the other four different double-threshold algorithms.

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