Spectrum optimization in Cognitive Radios using elitism in genetic algorithms

摘要

The availability of radio spectrum resource is becoming scarce with advancements in the communication applications. Most of the available spectrum has already been licensed and there would be a time when further developments in the field would be limited due to unavailability of this resource. Cognitive radio (CR) provides for the optimization of the available spectrum. The spectrum licensed is not utilized uniformly by the applications using it, rather the utilization is uneven with spaces that are not being utilized at all. Cognitive Radio identifies the spaces that are not in use at particular instant (empty frequencies) in the already licensed spectrum and reallocates them in order to accommodate new applications (secondary users) that can co-exist with the applications licensed to use that spectrum (primary users). Genetic Algorithms when implemented in the Cognitive Radios can provide for the required optimization in order to accommodate the secondary users in best possible space in the spectrum by interacting with the dynamic radio environment at real time. Elitism is used for selection of the best possible solutions among a pool of solutions. Elitism strives to prevent the loss of the best available solutions so that they make it to the next generation in the evolutionary genetic algorithms. This enables the decision-making process to compare the QoS requested by the secondary user with the sensed radio environment at each generation, to give an optimized solution.