• Nisha Morasada
• Ketki Pathak
• K.G. Bhuva

Wireless technologies have grown rapidly and needs more spectrum resources to support numerous emerging wireless services. Spectrum Sensing in cognitive radio (CR) protects the authorised user from the effect of pathetic interference that is caused by either cognitive users or other environmental parameters. In spectrum sensing there are two different challenges; first the CR has to detect channel under lower SNRs which increases the sensing time, and second is thatamong all CR nodes some nodes have experience the effect of deep fading and shadowing. So to solve this challenges Cooperative spectrum sensing is supposed to be used. But for CSS CRs needs extra energy to send the sensing result to the fusion centre and receive the final decision from the fusion centre. So this procedure increases the energy consumption. Therefore, CSS process may consume considerable energy from the battery of the CR node. Second-hand users (SU) of a cognitive radio station (CRN) are from healthy devices supplied by batteries, the sources of energy are relatively precious and it is desired that minimum power should be consumed from battery so it should be clear that one should use energy in a effective manner. In this paper different energy efficient algorithms are discussed like genetic algorithm and particle swarm optimization. Using this optimization techniques the overall energy consumption is reduced, and energy efficient cooperative spectrum sensing is done to maximize throughput.

Cognitive Radio Network, Co-operative spectrum sensing, Genetic Algorithm, Particle Swarm Optimization

"ENERGY EFFICIENT CO-OPERATIVE SPECTRUM SENSING USING GENETIC ALGORITHM AND PARTICAL SWARM OPTIMIZATION: A REVIEW", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 2, page no.463-469, February-2019, Available :http://www.jetir.org/papers/JETIRAB06080.pdf

"ENERGY EFFICIENT CO-OPERATIVE SPECTRUM SENSING USING GENETIC ALGORITHM AND PARTICAL SWARM OPTIMIZATION: A REVIEW", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 2, page no. pp463-469, February-2019, Available at : http://www.jetir.org/papers/JETIRAB06080.pdf