Spectrum sensing for Cognitive Radio using genetic algorithm

9Citations
Citations of this article
10Readers
Mendeley users who have this article in their library.

Abstract

Cognitive Radio has been skillful technology to improve the spectrum sensing as it enables Cognitive Radio to find Primary User (PU) and let secondary User (SU) to utilize the spectrum holes. However detection of PU leads to longer sensing time and interference. Spectrum sensing is done in specific "time frame" and it is further divided into Sensing time and transmission time. Higher the sensing time better will be detection and lesser will be the probability of false alarm. So optimization technique is highly required to address the issue of trade-off between sensing time and throughput. This paper proposed an application of Genetic Algorithm technique for spectrum sensing in cognitive radio. Here results shows that ROC curve of GA is better than PSO in terms of normalized throughput and sensing time. The parameters that are evaluated are throughput, probability of false alarm, sensing time, cost and iteration.

Cite

CITATION STYLE

APA

Kochar, S., & Garg, R. (2018). Spectrum sensing for Cognitive Radio using genetic algorithm. International Journal of Online Engineering, 14(9), 190–199. https://doi.org/10.3991/ijoe.v14i09.9064

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free