Throughput optimization in cognitive radio using demand based adaptive genetic algorithm

Cognitive radio is viewed as a novel approach and promising technology for improving the radio spectrum utilization. The cognitive radio is defined as an intelligent wireless communication approach that is aware of its environment. Spectrum sensing is one of the key functionality for cognitive radio (CR) systems to operate in the available spectrum holes. To guard the licensed users or primary users present in any spectrum from any interference, the CR should be able enough detect incumbent signals. In this paper the CR networks is studied in terms of throughput for different frequencies. The probability of detection, probability of false alarm and bit error probability are studied using a demand and need based genetic algorithm(GA), taking he geographical variations of the spectrum holes in consideration. The results shows that the proposed GA worked well and provides an appreciable solution to the cognitive radio network.