Arslan, Tughrul

Erdogan, Ahmet

Zuniga, Virgilio

Mexican National Council for Science and Technology (CONACyT)

2012-01-19T14:59:36Z

2012-01-19T14:59:36Z

2011-11-22

This thesis studies the effectiveness of bio-inspired optimization algorithms in controlling adaptive antenna arrays. Smart antennas are able to automatically extract the desired signal from interferer signals and external noise. The angular pattern depends on the number of antenna elements, their geometrical arrangement, and their relative amplitude and phases. In the present work different antenna geometries are tested and compared when their array weights are optimized by different techniques. First, the Genetic Algorithm and Particle Swarm Optimization algorithms are used to find the best set of phases between antenna elements to obtain a desired antenna pattern. This pattern must meet several restraints, for example: Maximizing the power of the main lobe at a desired direction while keeping nulls towards interferers. A series of experiments show that the PSO achieves better and more consistent radiation patterns than the GA in terms of the total area of the antenna pattern. A second set of experiments use the Signal-to-Interference-plus-Noise-Ratio as the fitness function of optimization algorithms to find the array weights that configure a rectangular array. The results suggest an advantage in performance by reducing the number of iterations taken by the PSO, thus lowering the computational cost. During the development of this thesis, it was found that the initial states and particular parameters of the optimization algorithms affected their overall outcome. The third part of this work deals with the meta-optimization of these parameters to achieve the best results independently from particular initial parameters. Four algorithms were studied: Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing and Hill Climb. It was found that the meta-optimization algorithms Local Unimodal Sampling and Pattern Search performed better to set the initial parameters and obtain the best performance of the bio-inspired methods studied.

http://hdl.handle.net/1842/5766

en

The University of Edinburgh

V. Zuniga, N. Haridas, A. T. Erdogan, and T. Arslan, “Effect of a central antenna element on the directivity, half-power beamwidth and sidelobe level of circular antenna arrays,” NASA/ESA Conference on Adaptive Hardware and Systems (AHS-2009), pp. 252–256, San Francisco, California, USA, July 29 - August 1 2009.

V. Zuniga, A. T. Erdogan, and T. Arslan, “Adaptive radiation pattern optimization for antenna arrays by phase perturbations using particle swarm optimization,” NASA/ESA Conference on Adaptive Hardware and Systems (AHS-2010), pp. 209–214, Anaheim, California, USA, June 15-18 2010.

V. Zuniga, A. T. Erdogan, and T. Arslan, “Control of adaptive rectangular antenna arrays using particle swarm optimization,” Loughborough Antennas & Propagation Conference (LAPC-2010), pp. 385–388, Loughborough UK, November 8-9 2010.

smart antenna

optimization algorithm

PSO

Particle Swarm Optimization

GA

Genetic Algorithm

Bio-inspired optimization algorithms for smart antennas

Thesis or Dissertation

Doctoral

PhD Doctor of Philosophy