Return to search

Design and modelling of beam steering antenna array for mobile and wireless applications using optimisation algorithms : simulation and measrement of switch and phase shifter for beam steering antenna array by applying reactive loading and time modulated switching techniques, optimised using genetic algorithms and particle swarm methods

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.

Identiferoai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:582994
Date January 2012
CreatorsAbusitta, Musa M.
ContributorsAbd-Alhameed, Raed A.; Excell, Peter S.
PublisherUniversity of Bradford
Source SetsEthos UK
Detected LanguageEnglish
TypeElectronic Thesis or Dissertation
Sourcehttp://hdl.handle.net/10454/5745

Page generated in 0.0022 seconds