Bio-inspired route estimation in cognitive radio networks

Cognitive radio is a technique that was originally created for the proper use of the radio electric spectrum due its underuse. A few methods were used to predict the network traffic to determine the occupancy of the spectrum and then use the ‘holes’ between the transmissions of primary users. The goal is to guarantee a complete transmission for the second user while not interrupting the trans-mission of primary users. This study seeks the multifractal generation of traffic for a specific radio electric spectrum as well as a bio-inspired route estimation for secondary users. It uses the MFHW algorithm to generate multifractal traces and two bio-inspired algo-rithms: Ant Colony Optimization and Max Feeding to calculate the secondary user’s path. Multifractal characteristics offer a predic-tion, which is 10% lower in comparison with the original traffic values and a complete transmission for secondary users. In fact, a hybrid strategy combining both bio-inspired algorithms promise a reduction in handoff. The purpose of this research consists on deriving future investigation in the generation of multifractal traffic and a mobility spectrum using bio-inspired algorithms

Modelo de propagación para un entorno urbano que identifica las oportunidades espectrales para redes móviles de radio cognitiva

El pronóstico de ocupación del espectro radioeléctrico es útil en el diseño de sistemas inalámbricos que aprovechan las oportunidades en el espectro como la radio cognitiva. En este documento se propone el desarrollo de un modelo de propagación, que a través del pronóstico de la potencia recibida, identifica las oportunidades espectrales en canales de una red móvil celular para un entorno urbano. El modelo propuesto integra un modelo de propagación a gran escala con un modelo neuronal wavelet, que combina las pérdidas promedio con las pérdidas instantáneas. Los resultados del modelo, obtenidos a través de simulaciones, son consistentes con el comportamiento observado en experimentos de este tipo de sistemas inalámbricos.Abstract. The forecast of the radioelectric spectrum occupancy is useful for wireless systems designs that take advantage of spectrum opportunities, such as cognitive radio. In this document the development of a propagation model is proposed, that through the forecasting of received power, identifies the spectral opportunities in channels of a cellular mobile network for an urban environment. The proposed model integrates a large-scale propagation model with a wavelet neural model, which combines the average losses with the instantaneous losses. The results of this model, which are obtained through simulations, are consistent with the behavior observed experimentally of this class of wireless systems.Doctorad