Antenas planares eletronicamente reconfiguráveis em frequência para sistemas de rádios cognitivos

Abstract

The effective usage of radio frequencies (RF) is a determining factor in the capacity of any mobile communications system. Improving the use of these resources has become very popular since the early days of these systems. The technologies and digital services have demanded higher RF allocation to meet bandwidth (BW) requirements. The development of emerging technologies based on dynamic RF allocation has been considered as a solution to this growing need for BW and motivation to carry out recent research on cognitive radio systems (CRS). In this work, UWB antennas are proposed for spectral sensing, as well as frequency reconfigurable antennas for CRS applications, which dynamically perform transmitting and receiving signals in narrowband (NB). Among the proposed prototypes, the presented models are able to cover the entire UWB spectrum from 3.1 GHz to 10.6 GHz. When working as reconfigurable antennas, the prototypes can cover the RF range in various NB, like 5.8 GHz. Moreover, the proposed antenna passed through optimization and synthesis processes based on computational intelligence tools. Genetic algorithm (GA), particle swarm optimization (PSO) algorithm, and artificial bee colony (ABC) algorithm are the used algorithms. As results, improved BW and the better antenna reflection coefficient were found. The computational simulations and the numerical analysis based on GA were performed using the HFSS software. In addition, numerical analyses with PSO and ABC algorithms were implemented in Java. For validation purposes, simulation results were compared with experimental results showing good agreement for all the proposed planar antennas prototypes developed in this work.