• Sarabpreet Kaur
• Simarpreet Kaur

Cognitive Radio is used to automatically determine the channels allocated in wireless frequency range and it alters the factors responsible for transmission which will further help in simultaneous many communications that helps in improving the efficient utilization of spectrum. Spectrum sensing is the major task to perform in cognitive radio. This study introduces a novel hybrid approach to perform spectrum sensing in an effective manner even in the presence of noise. The study is analyzed over different values of signal sampling size and noise uncertainty. The comparison analysis is done among proposed work, Energy Detection (ED), Covariance Absolute Value (CAV) and Joint Estimation mechanism. The results assure that the proposed work outperforms the traditional techniques.

Cognitive Radio, Spectrum Sensing, PSO optimization, GA Optimization, Probability of Detection.

"Optimization of Spectrum Sensing in Cognitive Radio Networks with Noise Uncertainty", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 6, page no.434-442, June-2018, Available :http://www.jetir.org/papers/JETIR1805814.pdf

"Optimization of Spectrum Sensing in Cognitive Radio Networks with Noise Uncertainty", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 6, page no. pp434-442, June-2018, Available at : http://www.jetir.org/papers/JETIR1805814.pdf