Design of cognitive engine for cognitive radio network using MOGA

The cognitive radio is a remote specialized gadget equipped able to sensing the surroundings and making choices on the way to use them to be had radio assets to permit communications with a certain Quality of Service(QoS). The cognitive engine is intelligent system background of the cognitive radio is a mishmash of optimization algorithms, spectrum sensing, and learning to adapt and control the radio system from the physical layer stack and up to the communication stack. This report explores the use of genetic algorithm optimization technique used by cognitive radios to decide upon a set of operating transmission parameters subject to a set of environmental parameters. A set transmission and environment parameters are used to define four communication objectives. A fitness function is designed using the communication objectives, the evaluation of which decides the best set of transmission parameters for successful communication. The result of this work is an analysis of the dependency of the communication objectives on different operating parameters and the implementation of a cognitive engine via simulation in MATLAB that uses MOGA (Multi objective GA) to decide upon transmission parameters.