TY  - JOUR
AU  - Chaudhary, Neha 
AU  - Mahajan, Rashima 
AU  - Adlakha, Richa 
AU  - Grover, Ashish 
AU  - Bansal, Dipali 
AU  - Bhatia, Sunny 
PY  - 2024
TI  - Enhanced Hybrid Spectrum Sensing Method Using TCDT and IEDT for Cognitive Radio
JF  - Journal of Computer Science
VL  - 20
IS  - 11
DO  - 10.3844/jcssp.2024.1486.1494
UR  - https://thescipub.com/abstract/jcssp.2024.1486.1494
AB  - The development of efficient spectrum sensing techniques has witnessed progressive growth for optimum utilization of spectrum resources in cognitive radio. The primary objective of spectrum sensing is the identification and proper utilization of the spectrum holes. Nowadays, due to the advancement of wireless technologies, the demand for spectrum is also increasing and thus in turn, the requirement for better spectrum sensing techniques. An attempt has been made to further improve the performance of spectrum sensing techniques for efficient primary user detection by implementing hybrid spectrum detection (a combination of two different spectrum sensing techniques). This study is comprised of an improved energy detector for message signals with a lower range of SNR and a third-order cyclostationary detection spectrum sensing technique for signals with a high value of SNR. A detailed comparative analysis of the implemented hybrid spectrum sensing technique with the individual spectrum sensing techniques and the existing hybrid spectrum sensing technique has been made A proposed scheme using Third order Cyclostationary-Detection Technique (TCDT) and Improved-Energy-Detection Technique (IEDT). Here, MATLAB software has been used for the implementation of TCDT with a low value of Signal-to-Noise Ratio (SNR) and IEDT has been employed for the signals with a high value of SNR. Simulation results of validation of the proposed hybrid spectrum sensing technique with conventional hybrid approaches reveal that the proposed technique outperforms the conventional hybrid spectrum sensing methods as it can improve the probability of detection from 17-45% with SNR values -15 to -25. It has also been analyzed that the probability of mis-detection decreases approximately from 18-47% with the SNR value range from -15 to -25. With a 0.1 value of the probability of a false alarm, there is a 47% deduction in the detection rate. Therefore, the proposed method possesses the capability to optimize the use of spectrum holes (unused frequency bands) for future cognitive radio.