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Abstract
Smart antenna alTay systems play a significant role in the development of wireless communication systems (WCS), improving system performance and capacity. An adaptive antenna array system changes its radiation pattern In accordance with the estimation and analysis of received signals, environment and pre-known information, using a set of adjustable parameters. Determination of suitable system parameters can be achieved through the application of heuristic optimization procedures.
ln this thesis, an overview of optimization methods is outlined. A detailed study of particle swarm optimization (PSO) algorithm is presented. Usually, the required target is varying with time. Modification to PSO algorithm is proposed to support solving dynamic real time varying target problems efficiently. ln addition, a mapping technique to convert the constrained search space to an unbounded one is introduced. Using such conversion enhances PSO algorithm to handle constrained search problems in reduced time.
An overall review of smart antenna systems applications and vanous architectures are presented. Different beamforming and direction of arrival (DOA) signal estimation algorithms are reviewed. Simulation using PSO algorithm to solve different beamforming and array signal processing scenarios is applied. PSO algorithm efficiency in handling the problem through controlling different design parameters is explored. Constrained parameters radiation pattern synthesis using PSO algorithm is studied. The use of Modified Dynamic PSO algorithm to cope with changing required pattern problem is illustrated.
Direct Data Domain Least Squares (D3LS) approach, a pre-processing method to estimate incoming signal using PSO algorithm is presented. An extension is
suggested to the D3LS technique to utilize all antenna array elements in signal estimation, rather than half of them in the original method, is investigated and proved its efficiency for providing more accurate solution.