Implementation of Resource Allocation Algorithm for Cognitive Radio Systems

Abstract

Due to the increase in communication techniques, Radio spectrum has become a scarce resource. Based on the information available from the spectrum in the area, Cognitive Radio (CR) networks determine the usage of bandwidth by adjusting its transmission. It automatically detects the usage of the spectrum and decides how to use the available resources. Few newly adapted devices try to utilize the unused spectrum which is the main idea behind the cognitive radio network working. It can transmit signals according the noise, interference and variations in the channel. When the channel will be idle, that will be sensed by the CR and it tries to allocate that spectrum to some user in need. CR operation is completely based on the SDR. Here we are using optimization technique based on evolutionary algorithms to utilize the available resources and to allocate them to the users in need. Here the evolutionary algorithms used are particle swarm optimization (PSO), Modified PSO (MPSO) and kinetic gas molecular optimization (KGMO). We have simulated subcarrier allocation and power allocation of all three algorithms and checked which algorithm helps in better resource allocation. Simulation results also show capacity of each user and also comparing with other algorithms.