Reconfigurable Antenna Design And Its Optimization Using Hybrid Soft Computing

Abstract

As communication devices become smaller and smaller due to advancement of nanotechnology, the antenna become significantly larger part of overall package volume. Also antennas have various limitations like their limited gain, directivity, lack of adaptive reconfigurability. So there is always a requirement of small size, high gain and reconfigurable antenna for wireless communication mainly for personal communication, satellite communications and biomedical applications. Therefore, the scope of the research encompasses the designing of reconfigurable microstrip patch antenna that can be used in present and future wireless communication system. In this thesis work, author presents a design of frequency reconfigurable planar microstrip rectangular patch antenna. To make antenna reconfigurable, antenna is loaded with split ring resonator metamaterial structure. MTM is an artificial material engineered to have properties that may not be found in nature. MTM shows simultaneously negative values of permittivity and permeability values over a common frequency band. Equilateral triangular shaped SRR structure is used as an antenna. The structure is made tunable by rotation of inner and outer ring. newlineAccurate design and optimal output are the demands of present day wireless industries. Nature inspired soft computing such as bacterial foraging optimization, particle swarm optimization are the upcoming optimization techniques of recent times which have drawn the attention of researchers. In the thesis, author has used intelligent bacterial foraging optimization algorithm which is hybridization of BFO and PSO soft computing technique to optimize the design. By using IBFOA, the length of SRR is optimized so that loaded antenna resonant in the frequency regime in which isolated SRR shows metamaterial properties. By introducing micro-splits and hence changing the reactance of structure, frequency tunability has been achieved. newline