scholarly journals An Efficient Approach for Sidelobe Level Reduction Based on Recursive Sequential Damping

Symmetry ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 480
Author(s):  
Yasser Albagory ◽  
Fahad Alraddady
Keyword(s):  
Communication Systems ◽  
Optimization Techniques ◽  
Wireless Communication Systems ◽  
Sidelobe Level ◽  
Pattern Synthesis ◽  
Essential Requirement ◽  
Planar Arrays ◽  
Uniform Array ◽  
And Performance ◽  
Sidelobe Level Reduction

Recently, antenna array radiation pattern synthesis and adaptation has become an essential requirement for most wireless communication systems. Therefore, this paper proposes a new recursive sidelobe level (SLL) reduction algorithm using a sidelobe sequential damping (SSD) approach based on pattern subtraction, where the sidelobes are sequentially reduced to the optimum required levels with near-symmetrical distribution. The proposed SSD algorithm is demonstrated, and its performance is analyzed, including SLL reduction and convergence behavior, mainlobe scanning, processing speed, and performance under mutual coupling effects for uniform linear and planar arrays. In addition, the SSD performance is compared with both conventional tapering windows and optimization techniques, where the simulation results show that the proposed SSD approach has superior maximum and average SLL performances and lower processing speeds. In addition, the SSD is found to have a constant SLL convergence profile that is independent on the array size, working effectively on any uniform array geometry with interelement spacing less than one wavelength, and deep SLL levels of less than −70 dB can be achieved relative to the mainlobe level, especially for symmetrical arrays.

Application of the Unit Circle Representation to Pattern Synthesis of Nonuniformly Spaced and Nonuniformly Excited Arrays based on the Teaching Learning Based Optimization

2019 ◽  
Vol 4 (1) ◽  
pp. 8-17
Author(s):  
Abdelmadjid RECIOUI
Keyword(s):  
Unit Circle ◽  
Antenna Array ◽  
Communication Systems ◽  
Sidelobe Level ◽  
Pattern Synthesis ◽  
Linear Arrays ◽  
Array Pattern ◽  
Teaching Learning Based Optimization ◽  
Null Placement ◽  
Teaching Learning

Pattern synthesis of Antenna array has gained much attention over the last years as they constitute an important role in the modern communication systems. Unit circle-based techniques such as Schelkunoff null placement method have proved their effectiveness to synthesize uniformly spaced linear arrays. Nonuniformly spaced antenna array pattern synthesis has been investigated and interesting results have been obtained. In this work, the unit circle representation approach is applied to synthesize nonuniformly spaced and nonuniformly excited linear arrays. The objective is to accurately place nulls in the desired directions while achieving the least possible sidelobe level. The problem is cast as an optimization problem that is solved using the Teaching Learning Based Optimization (TLBO). Examples are dealt with to prove the design approach effectiveness and flexibility for modern communication system applications.

Performance Evaluation of Elliptical-Cylindrical Antenna Array using SaDE Optimized Hyper Beam

2017 ◽  
Vol 7 (1) ◽  
pp. 178 ◽  
Author(s):  
Gebrehiwet Gebrekrstos Lema
Keyword(s):  
Communication Systems ◽  
High Performance ◽  
Optimization Technique ◽  
Analytical Techniques ◽  
Side Lobe ◽  
Optimization Techniques ◽  
Side Lobe Level ◽  
Pattern Synthesis ◽  
Improved Performance ◽  
The Individual

<p>For high performance communication systems, Side Lobe Level (SLL) reduction and improved directivity are the goal of antenna designers. In the recent years, many optimization techniques of antenna design are occupying demanding place over the analytical techniques. Though they have contributed attractive solutions, it is often obvious to select one that meets the particular design need at hand. In this paper, an optimization technique called Self-adaptive Differential Evolution (SaDE) that can be able to learn and behave intelligently along with hyper beam forming is integrated to determine an optimal set of excitation weights in the design of EcAA. Non-uniform excitation weights of the individual array elements of EcAA are performed to obtain reduced SLL, high directivity and flexible radiation pattern. To evaluate the improved performance of the proposed SaDE optimized hyper beam, comparison are done with uniformly excited, SaDE without hyper beam and Genetic Algorithm (GA). In general, the proposed work of pattern synthesis has resulted in much better reduction of SLL and FNBW than both the uniformly excited and thinned EcAA. The results of this study clearly reveal that the SLL highly reduced at a very directive beamwidth.</p>

scholarly journals Optimal Pattern Synthesis of Linear Antenna Array Using Grey Wolf Optimization Algorithm

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Prerna Saxena ◽  
Ashwin Kothari
Keyword(s):  
Antenna Arrays ◽  
Side Lobe ◽  
Optimization Techniques ◽  
Main Beam ◽  
Linear Antenna ◽  
Grey Wolf ◽  
Grey Wolf Optimization ◽  
Pattern Synthesis ◽  
Uniform Array ◽  
Linear Antenna Arrays

The aim of this paper is to introduce the grey wolf optimization (GWO) algorithm to the electromagnetics and antenna community. GWO is a new nature-inspired metaheuristic algorithm inspired by the social hierarchy and hunting behavior of grey wolves. It has potential to exhibit high performance in solving not only unconstrained but also constrained optimization problems. In this work, GWO has been applied to linear antenna arrays for optimal pattern synthesis in the following ways: by optimizing the antenna positions while assuming uniform excitation and by optimizing the antenna current amplitudes while assuming spacing and phase as that of uniform array. GWO is used to achieve an array pattern with minimum side lobe level (SLL) along with null placement in the specified directions. GWO is also applied for the minimization of the first side lobe nearest to the main beam (near side lobe). Various examples are presented that illustrate the application of GWO for linear array optimization and, subsequently, the results are validated by benchmarking with results obtained using other state-of-the-art nature-inspired evolutionary algorithms. The results suggest that optimization of linear antenna arrays using GWO provides considerable enhancements compared to the uniform array and the synthesis obtained from other optimization techniques.

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