Spectrum Optimization in Cognitive Radio Networks using Genetic Algorithms

Abstract: The rapid revolution in wireless communication in past years has increased the demand of radio spectrum to fulfill quality of service (QoS) requirements of wireless applications, leading to spectrum overcrowding. To solve the spectrum overcrowding problem, cognitive radio (CR) has emerged as a leading technology because it can intelligently sense an unused spectrum without creating any harm to authorized users. Once the spectrum is sensed, to fulfill QoS requirement of the application and to utilize the radio resources more efficiently, an intelligent decision to allocate an optimum spectrum is a prime requirement. In this thesis work a spectrum allocation procedure is proposed. Genetic Algorithms (GA) an evolutionary computational technique is used which works on Darwin theory of evolution. It defines the radio in the form of chromosomes and genes. The procedure is modeled using Matlab, and the application’s QoS requirements are given as input to the GA procedure, which results in an optimum solution after several evolution