Memetic Algorithms for Optimizing Adaptive Linear Array Patterns by Phase-Position Perturbation |
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Authors: | Chao-Hsing Hsu Wen-Jye Shyr |
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Affiliation: | (1) Department of Electronic Engineering, Chienkuo Technology University, Changhua 500, Taiwan, Republic of China;(2) Department of Industrial Education and Technology, National Changhua University of Education, Changhua 500, Taiwan, Republic of China |
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Abstract: | In this paper, based on the phase-position perturbation method, an
innovative optimal adaptive antenna technique is proposed, where the
deduced radiation pattern formulas available for searching optimal
solutions are used to search the optimal weighting vector. The
optimal radiation pattern designs of adaptive antenna are studied by
the phase-position perturbation method. Memetic algorithms are used to
search the optimal weighting vector of the phase-position
perturbations for the array factor. The design for an optimal
radiation pattern of an adaptive antenna can not only adjustably
suppress the interferers by placing nulls at the directions of the
interfering sources, but at the same time provide a maximum main
lobe in the direction of the desired signal, i.e., to maximize the
signal-to-interference ratio. To achieve this goal, a
new convergent method, referred to as the two-way convergent method
for memetic algorithms, is proposed. The memetic algorithm combines
a genetic algorithm and local search heuristics to solve combinatorial
optimization problems. The memetic algorithm is a kind of improved
type of the traditional genetic algorithm. By using a local search
procedure, it can avoid the shortcomings of the traditional genetic
algorithm, whose termination criteria are set up by using the trial
and error method. This proposed method is also able to solve the
multipath problem, which exists at the same time in this
communication system. The optimal radiation pattern concept can be
implemented in practical wireless communication systems. Simulation
results are also given in this paper. |
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Keywords: | |
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