scholarly journals Heterogeneous Spectrum Sensing in Cognitive Radio Network using Traditional Energy Detection and Matched Filter

2017 ◽  
Vol 02 (08) ◽  
pp. 259-263
Author(s):  
Shahbaz Soofi ◽  
2014 ◽  
Vol 17 (1) ◽  
pp. 17-31
Author(s):  
Tu Thanh Nguyen ◽  
Khoa Le Dang ◽  
Thu Thi Hong Nguyen ◽  
Phuong Huu Nguyen

In cognitive radio network, how to minimize the impact of secondary user on primary user’s signal plays a very important and complex role. Therefore, spectrum sensing is one of the most essential components of cognitive radio. Therefore, the effect of spectrum sensing algorithms plays a key role to the system’s performance. In this paper, we concentrate on spectrum sensing algorithms in order to find out spectrum hole or while hole for reusing it. Specifically, we will highlight the energy detector algorithm of unknown deterministic signals over fading channels. The numerical results match well with theoretical analysis. The system’s performance of energy detection in AWGN channel is acceptable in case of relatively low signal to noise ratio (SNR). However, the performance of system will be degraded remarkable over fading environments.


2021 ◽  
Vol 11 (2) ◽  
pp. 1349-1361
Author(s):  
Kandlagunta Tejesh

Aim: The study aims to detect the effective channel in cognitive radio network at low SNR using an innovative algorithm based on matched filter detection and compared it with energy detection. Materials and methods: The spectrum sensing based on novel matched filter detection with 10 samples is compared with the energy detection by varying the SNR conditions, using MATLAB. Results: The probability of detection of the matched filter is high at low SNR(-30db) then compared to the probability of detection of energy detection at low SNR(-10db) and the significance level is 0.002, i.e., (P<0.05) which gives better sensing performance. Conclusion: this would be proved to conclude that at low SNR conditions the matched filter detection gives significantly high sensing probability.


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