The objectives of this work were to investigate, design and implement beam steering antenna arrays for
mobile and wireless applications using the genetic algorithm (GA) and particle swarm optimisation (PSO)
techniques as optimisation design tools. Several antenna designs were implemented and tested: initially, a
printed dipole antenna integrated with a duplex RF switch used for mobile base station antenna beam
steering was investigated. A coplanar waveguide (CPW) to coplanar strip (CPS) transition was adopted to
feed the printed dipole. A novel RF switch circuit, used to control the RF signal fed to the dipole antenna
and placed directly before it, was proposed. The measured performance of the RF switch was tested and
the results confirmed its viability. Then two hybrid coupled PIN diode phase shifters, using Branchline
and Rat-Race ring coupler structures, were designed and tested. The generation of four distinct phase
shifts was implemented and studied. The variations of the scattering parameters were found to be realistic,
with an acceptable ±2 phase shift tolerance.
Next, antenna beam steering was achieved by implementing RF switches with ON or OFF mode
functions to excite the radiating elements of the antenna array. The switching control process was
implemented using a genetic algorithm (GA) method, subject to scalar and binary genes. Anti-phase
feeding of radiating elements was also investigated. A ring antenna array with reflectors was modelled
and analysed. An antenna of this type for mobile base stations was designed and simulation results are
presented.
Following this, a novel concept for simple beam steering using a uniform antenna array operated at 2.4
GHz was designed using GA. The antenna is fed by a single RF input source and the steering elements
are reactively tuned by varactor diodes in series with small inductors. The beam-control procedure was
derived through the use of a genetic algorithm based on adjusting the required reactance values to obtain
the optimum solution as indicated by the cost function. The GA was also initially used as an optimisation
tool to derive the antenna design from its specification.
Finally, reactive loading and time modulated switching techniques are applied to steer the beam of a
circular uniformly spaced antenna array having a source element at its centre. Genetic algorithm (GA)
and particle swarm optimisation (PSO) processes calculate the optimal values of reactances loading the
parasitic elements, for which the gain can be optimised in a desired direction. For time modulated
switching, GA and PSO also determine the optimal on and off times of the parasitic elements for which
the difference in currents induced optimises the gain and steering of the beam in a desired direction.
These methods were demonstrated by investigating a vertically polarised antenna configuration. A
prototype antenna was constructed and experimental results compared with the simulations. Results
showed that near optimal solutions for gain optimisation, sidelobe level reduction and beam steering are
achievable by utilising these methods. In addition, a simple switching process is employed to steer the
beam of a horizontally polarised circular antenna array. A time modulated switching process is applied
through Genetic Algorithm optimisation. Several model examples illustrate the radiation beams and the
switching time process of each element in the array.
Identifer | oai:union.ndltd.org:BRADFORD/oai:bradscholars.brad.ac.uk:10454/5745 |
Date | January 2012 |
Creators | Abusitta, M.M. |
Contributors | Abd-Alhameed, Raed, Excell, Peter S. |
Publisher | University of Bradford, School of Engineering, Design and Technology |
Source Sets | Bradford Scholars |
Language | English |
Detected Language | English |
Type | Thesis, doctoral, PhD |
Rights | <a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/3.0/"><img alt="Creative Commons License" style="border-width:0" src="http://i.creativecommons.org/l/by-nc-nd/3.0/88x31.png" /></a><br />The University of Bradford theses are licenced under a <a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/3.0/">Creative Commons Licence</a>. |
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