Optimal Resource Allocation Strategy Using Energy Efficient Optimized Clustering With Genetic Optimization In Cooperative CRN's
Now we are in the era of 4G technologies but as per the advancement in technology the expectations of users from the network increased resulting available unlicensed radio spectrum crowded day by day. As a result the usages of unlicensed spectrum are increased and On the other hand the licensed spectrums are underutilized results in spectrum scarcity. So the cognitive radio is the technique which intelligently senses the environment and gives the opportunity to the unlicensed users to access
... users to access the licensed band under some conditions. The one of the main target in cognitive radio is to sense the environment and to find the spectrum hole known as spectrum sensing. The energy consumption is the main factor when we consider the spectrum sensing in the cognitive radio because the cognitive radios are basically low power sensors. There are two types of spectrum sensing i.e. non cooperative and cooperative. In the non cooperative spectrum sensing scheme the energy consumption is more as that of cooperative spectrum sensing technique because it generates the result by cooperating all other local sensing nodes. In this research main aim is to design energy efficient spectrum sensing algorithms keeping in mind the end goal to limit the maximum energy consumption. For this we design optimal clustering by using an artificial intelligence like genetic algorithm which is one of the inspired techniques by evolutionary and biological behavior. In our model the cluster heads are re-established in each round so that the load is well distributed among all the nodes of the network resulting energy efficiency and increased lifetime of the network.