Application of the Spiral Optimization Technique to Antenna Array Design

2018 ◽  
pp. 364-385
Author(s):  
Abdelmadjid Recioui
Keyword(s):  
Global Optimization ◽  
Antenna Array ◽  
Antenna Arrays ◽  
Optimization Technique ◽  
Excitation Amplitude ◽  
Optimization Method ◽  
Side Lobe ◽  
Population Based ◽  
Optimization Task ◽  
Optimization Methodology

Antenna arrays are considered as important type used in today's long-distance communication. The design of such antenna depends on parameters and desired behavior performing the task. This chapter deals with the application of a new type of nature-inspired global optimization methodology in the design of an optimized planar antenna array which ensures minimum side lobes and high directivity, this new optimization method is Spiral optimization technique which is a population based iterative heuristic global optimization algorithm technique for multi-dimensional and multi-modal problems with the potential to implement constraints on the search domain. The optimization task results in a good suppression of the side lobe level for the different antenna configurations with several sorts of excitation: Amplitude only, phase only, both amplitude and phase. Besides, the directivity is not worse than that of the conventional uniform one.

Rectangular Antenna Array Optimization using Wind Driven Optimization

2021 ◽  
Vol 1 (2) ◽  
pp. 109-120
Author(s):  
Abdelmadjid Recioui ◽  
Mondher Benabid ◽  
Nabil Djilani
Keyword(s):  
Global Optimization ◽  
Antenna Array ◽  
Antenna Arrays ◽  
Excitation Amplitude ◽  
Optimization Method ◽  
Side Lobe ◽  
High Gain ◽  
Population Based ◽  
Side Lobe Level ◽  
Long Distance

Antenna arrays are considered as important type used today for long distance communication with a very high gain. The design of such antenna depends on parameters and desired behavior performing the task, this project handle the application of a new type of nature-inspired global optimization methodology in the design of an optimized planar antenna array which ensures minimum side lobes and high directivity, this new optimization method is based on the atmospheric motion and it is known as Wind Driven Optimization (WDO) a population based iterative heuristic global optimization algorithm technique for multi-dimensional and multi-modal problems with the potential to implement constraints on the search domain. The optimal values obtained results in a good suppression of the side lobe level for the different antenna configurations with several sorts of excitation: Amplitude only, phase only, both amplitude and phase. Besides, the directivity is not worse than that of the uniform one.

scholarly journals 3D Antenna Array Design using Firefly Optimization Algorithm

2019 ◽  
Vol 4 (2) ◽  
pp. 61-70
Author(s):  
Abdelmadjid RECIOUI ◽  
Youcef GRAINAT
Keyword(s):  
Global Optimization ◽  
Antenna Array ◽  
Antenna Arrays ◽  
Optimization Algorithm ◽  
Optimization Technique ◽  
Optimization Method ◽  
Side Lobe ◽  
Population Based ◽  
Synthesis Process ◽  
Side Lobe Level

The design of antenna arrays in a 3D geometry is presented in this Chapter. The decision variables considered for this synthesis problem are the array element amplitude excitations. The objective is to design an array which ensures minimum sidelobe level and a high directivity. The synthesis process is carried out using a nature-inspired global optimization technique. The optimization method based on the reaction of a firefly to the light of other fireflies is known as Firefly Algorithm (FA). It is a population-based iterative heuristic global optimization algorithm technique, developed by Xin-She Yang, for multi-dimensional and multi-modal problems. Simulation results for an antenna array with isotropic elements show that side lobe level is significantly reduced in non-uniform case. Besides, the directivity is not worse than that of the uniform one.

Optimum design of linear and circular antenna arrays using equilibrium optimization algorithm

2021 ◽  
pp. 1-12
Author(s):  
Ali Durmus ◽  
Rifat Kurban
Keyword(s):  
Antenna Array ◽  
Radiation Pattern ◽  
Antenna Arrays ◽  
Optimization Algorithm ◽  
Communication Systems ◽  
Control Volume ◽  
Optimization Technique ◽  
Beam Width ◽  
Side Lobe ◽  
Side Lobe Level

Abstract In this paper, equilibrium optimization algorithm (EOA), which is a novel optimization algorithm, is applied to synthesize symmetrical linear antenna array and non-uniform circular antenna array (CAA). The main purpose of antenna array synthesis is to achieve a radiation pattern with low maximum side lobe level (MSL) and narrow half-power beam width (HPBW) in far-field. The low MSL here is an important parameter to reduce interference from other communication systems operating in the same frequency band. A narrow HPBW is needed to achieve high directionality in antenna radiation patterns. Entering the literature as a novel optimization technique, EOA optimally determined the amplitude and position values of the array elements to obtain a radiation pattern with a low MSL and narrow HPBW. The EOA is inspired by models of the control volume mass balance used to predict equilibrium as well as dynamic states. To demonstrate the flexibility and performance of the proposed algorithm, 10-element, 16-element and 24-element linear arrays and eight-element, 10-element and 12-element CAAs are synthesized. The MSL and HPBW values of radiation pattern obtained with the EOA are very successful compared to the results of other optimization methods in the literature.

scholarly journals Optimum design of non-uniform symmetrical linear antenna arrays using a novel modified invasive weeds optimization

2016 ◽  
Vol 65 (1) ◽  
pp. 5-18 ◽  
Author(s):  
El Hadi Kenane ◽  
Farid Djahli
Keyword(s):  
Antenna Arrays ◽  
Optimization Technique ◽  
Optimization Method ◽  
Good Alternative ◽  
Side Lobe ◽  
Good Choice ◽  
Side Lobe Level ◽  
Invasive Weeds ◽  
Linear Antenna ◽  
Linear Antenna Arrays

Abstract This paper presents a new modified method for the synthesis of non-uniform linear antenna arrays. Based on the recently developed invasive weeds optimization technique (IWO), the modified invasive weeds optimization method (MIWO) uses the mutation process for the calculation of standard deviation (SD). Since the good choice of SD is particularly important in such algorithm, MIWO uses new values of this parameter to optimize the spacing between the array elements, which can improve the overall efficiency of the classical IWO method in terms of side lobe level (SLL) suppression and nulls control. Numerical examples are presented and compared to the existing array designs found in the literature, such as ant colony optimization (ACO), particle swarm optimization (PSO), and comprehensive learning PSO (CLPSO). Results show that MIWO method can be a good alternative in the design of non-uniform linear antenna array.

scholarly journals Null Steering in Failed Antenna Arrays

2011 ◽  
Vol 2011 ◽  
pp. 1-9 ◽  
Author(s):  
Om Prakash Acharya ◽  
Amalendu Patnaik ◽  
Sachendra N. Sinha
Keyword(s):  
Antenna Array ◽  
Antenna Arrays ◽  
Side Lobe ◽  
Side Lobe Level ◽  
Correction Procedure ◽  
Swarm Optimization ◽  
Array Pattern ◽  
Null Steering ◽  
Simulation Results ◽  
Pattern Simulation

Antenna array pattern nulling is desirable in order to suppress the interfering signals. But in large antenna arrays, there is always a possibility of failure of some elements, which may degrade the radiation pattern with an increase in side lobe level (SLL) and removal of the nulls from desired position. In this paper a correction procedure is introduced based on Particle Swarm Optimization (PSO) which maintains the nulling performance of the failed antenna array. Considering the faulty elements as nonradiating elements, PSO reoptimizes the weights of the remaining radiating elements to reshape the pattern. Simulation results for a Chebyshev array with imposed single, multiple, and broad nulls with failed antenna array are presented.

A Comparison of Swarm-Based Optimization Algorithms in Linear Antenna Array Synthesis

2021 ◽  
Author(s):  
Ali Durmus ◽  
Rifat KURBAN ◽  
Ercan KARAKOSE
Keyword(s):  
Antenna Array ◽  
Radiation Pattern ◽  
Antenna Arrays ◽  
Heuristic Algorithms ◽  
Beam Width ◽  
Side Lobe ◽  
Side Lobe Level ◽  
Linear Antenna ◽  
Half Power ◽  
Antenna Array Synthesis

Abstract Today, the design of antenna arrays is very important in providing effective and efficient wireless communication. The purpose of antenna array synthesis is to obtain a radiation pattern with low side lobe level (SLL) at a desired half power beam width (HPBW) in far-field. The amplitude and position values ​​of the array elements can be optimized to obtain a radiation pattern with suppressed SLLs. In this paper swarm-based meta-heuristic algorithms such as Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), Mayfly algorithm (MA) and Jellyfish Search (JS) algorithms are compared to realize optimal design of linear antenna arrays. Extensive experiments are conducted on designing 10, 16, 24 and 32-element linear arrays by determining the amplitude and positions. Experiments are repeated 30 times due to the random nature of swarm-based optimizers and statistical results show that performance of the novel algorithms, MA and JS, are better than well-known methods PSO and ABC.

A review on optimization of antenna array by evolutionary optimization techniques

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
D.D. Devisasi Kala ◽  
D. Thiripura Sundari
Keyword(s):  
Antenna Array ◽  
Antenna Arrays ◽  
Optimization Algorithm ◽  
Firefly Algorithm ◽  
Side Lobe ◽  
Optimization Techniques ◽  
Swarm Optimization ◽  
Content Type ◽  
Gain Enhancement ◽  
Whale Optimization

PurposeOptimization involves changing the input parameters of a process that is experimented with different conditions to obtain the maximum or minimum result. Increasing interest is shown by antenna researchers in finding the optimum solution for designing complex antenna arrays which are possible by optimization techniques.Design/methodology/approachDesign of antenna array is a significant electro-magnetic problem of optimization in the current era. The philosophy of optimization is to find the best solution among several available alternatives. In an antenna array, energy is wasted due to side lobe levels which can be reduced by various optimization techniques. Currently, developing optimization techniques applicable for various types of antenna arrays is focused on by researchers.FindingsIn the paper, different optimization algorithms for reducing the side lobe level of the antenna array are presented. Specifically, genetic algorithm (GA), particle swarm optimization (PSO), ant colony optimization (ACO), cuckoo search algorithm (CSA), invasive weed optimization (IWO), whale optimization algorithm (WOA), fruitfly optimization algorithm (FOA), firefly algorithm (FA), cat swarm optimization (CSO), dragonfly algorithm (DA), enhanced firefly algorithm (EFA) and bat flower pollinator (BFP) are the most popular optimization techniques. Various metrics such as gain enhancement, reduction of side lobe, speed of convergence and the directivity of these algorithms are discussed. Faster convergence is provided by the GA which is used for genetic operator randomization. GA provides improved efficiency of computation with the extreme optimal result as well as outperforming other algorithms of optimization in finding the best solution.Originality/valueThe originality of the paper includes a study that reveals the usage of the different antennas and their importance in various applications.

Synthesis of thinned planar antenna arrays using teaching–learning-based optimization

2014 ◽  
Vol 7 (5) ◽  
pp. 557-563 ◽  
Author(s):  
Nihad I. Dib
Keyword(s):  
Antenna Arrays ◽  
Optimization Problems ◽  
Optimization Method ◽  
Side Lobe ◽  
Side Lobe Level ◽  
Planar Antenna ◽  
Teaching Learning Based Optimization ◽  
Teaching Learning ◽  
Level Reduction ◽  
Better Than

In this paper, the design of thinned planar antenna arrays of isotropic radiators with optimum side lobe level reduction is studied. The teaching–learning-based optimization (TLBO) method, a newly proposed global evolutionary optimization method, is used to determine an optimum set of turned-ON elements of thinned planar antenna arrays that provides a radiation pattern with optimum side lobe level reduction. The TLBO represents a new algorithm for optimization problems in antenna arrays design. It is shown that the TLBO provides results that are better than (or the same as) those obtained using other evolutionary algorithms.

A Crossover Improved Genetic Algorithm and Its Application in Non-Uniform Linear Antenna Arrays

2017 ◽  
Vol 16 (04) ◽  
pp. 1750027 ◽  
Author(s):  
Bhargav Appasani ◽  
Rahul Pelluri ◽  
Vijay Kumar Verma ◽  
Nisha Gupta
Keyword(s):  
Genetic Algorithm ◽  
Antenna Arrays ◽  
Optimization Technique ◽  
Beam Width ◽  
Side Lobe ◽  
Optimization Techniques ◽  
Linear Antenna ◽  
Improved Genetic Algorithm ◽  
Element Array ◽  
Linear Antenna Arrays

Genetic Algorithm (GA) is a widely used optimization technique with multitudinous applications. Improving the performance of the GA would further augment its functionality. This paper presents a Crossover Improved GA (CIGA) that emulates the motion of fireflies employed in the Firefly Algorithm (FA). By employing this mimicked crossover operation, the overall performance of the GA is greatly enhanced. The CIGA is tested on 14 benchmark functions conjointly with the other existing optimization techniques to establish its superiority. Finally, the CIGA is applied to the practical optimization problem of synthesizing non-uniform linear antenna arrays with low side lobe levels (SLL) and low beam width, both requirements being incompatible. However, the proposed CIGA applied for the synthesis of a 12 element array yields an SLL of [Formula: see text]29.2[Formula: see text]dB and a reduced beam width of 19.1[Formula: see text].

Sign in / Sign up

Export Citation Format

Share Document