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The radiation pattern and other electrical characteristics of an antenna primarily depend on its
size and geometry. In the current age of communications, it is highly desirable to have compact
and light weight communication devices. Therefore the most challenging issue of today’s
wireless communication systems is to design antennas which are cost effective and of compact
size without compromising the radiating efficiency and effectiveness.
Since microstrip patch antennas are light weight, compact, easy to design and install; they are the
best choice for today’s communication devices. That’s why patch antennas are widely used in
numerous wireless applications as a single radiating element and as an array of multiple
elements. However, designing of different shaped antennas to suit the electrical and/or physical
requirements of the communication system is not an easy task.
In this dissertation we have successfully designed microstrip patch antennas to achive desired
electrical charcteristics such as frequency, bandwidth and quality factor alongwith the targeted
physical characteristics such as length, radius or area etc. Keeping in mind the utilization of
various shapes of antennas in communication systems; the dissertation includes designing of
different geometrical shaped patch antennas such as square, circular and hexagonal.
In addition to design patch antennas, we have succefully designed array of patch elements to be
used in MIMO systems. The array has been designed for the desired electrical characteristics
such as directivity, frequency, and return loss etc.
Moreover, using this array design model, we estimated the channel capacity for ferquency
selective Rayleigh fading channel. Since ultra wide band frequency systems are suitable for high
data rates with low power consumption, we have particularly focused on this range of frequncy
for antenna designing.
Among all the heuristic approaches, literature shows that particle swarm optimization (PSO) and
genetic algorithm (GA) are the most efficient and effective heuristic approaches in solving the
problems of antenna and electromagnetics. Therefore we have employed these two approaches
for designing and optimizing these antennas.
We have also developed a new heuristic algorithm namely Wildebeest Herd Optimization (WHO)
algorithm. It is based on the living wildebeest in their herd and migrating from one point to
another for food and water. All the multi-geometrical antennas have been designed and
optimized on WHO in addition to GA and PSO. The comparative analysis verifies that the
proposed algorithm is more effective and efficient than the existing heuristic approaches.
Moreover, artificial neural network (ANN) is employed to model the electrical/magnetic
behavior of single antenna and arrays. The outcome of ANN models are compared with the
results of numerical computational software Ansoft HFSS. In the light of this work, various
future recommendations are also given at the end. |
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