Research Article Open Access

Optimization of Cognitive Radio Sensing Techniques Using G enetic Algorithm

Abstract

Cognitive radio technology is a low cost communication system. The main reason of choosing the cognitive system is that it prevents the interfering of licensed and authorised users; by choosing the available frequencies and waveforms automatically Today the development of the new radio technologies is limited because of the available radio spectrum. But the spectrum sensing is the vital technology in the radio networks. It enhances the spectral efficiency by filling the wireless spectrum voids.The code is written for cognitive radio architecture. In this architecture, a maximum of 300 nodes is taken as an architectural network. The aim of this work is to find the secondary users if the primary user is unable to transfer the data load which is provided to it. The problem of searching a secondary node is quite common in terms of cognitive radio networks. An optimal search method has been opted using GENETIC ALGORITHM. The genetic algorithm has three phases namely, Mutation – Cross-over, Objective Function and the fitness function .The mutation checks when the state of a node in the network changes. First of all node ids of all the nodes in the network is created .Further more if any id is repeated in the sequence , it is changed accordingly . When the data transfer comes into action and the primary user is not able to take the data load, Genetic algorithm is called, on the basis of the energy of the nodes, which are getting transferred from one end to another end. If the energy of the searched node is less than that of the threshold of the entire network then it is added to the objective function list else the node is ignored. The whole simulation is done in MATLAB 7.10 environment

Supreet Kaur, Inderdeep Kaur Aulakh

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