scholarly journals A Novel Modified Sparrow Search Algorithm with Application in Side Lobe Level Reduction of Linear Antenna Array

2021 ◽  
Vol 2021 ◽  
pp. 1-25
Author(s):  
Qiankun Liang ◽  
Bin Chen ◽  
Huaning Wu ◽  
Chaoyi Ma ◽  
Senyou Li
Keyword(s):  
Antenna Array ◽  
Antenna Arrays ◽  
Search Algorithm ◽  
Side Lobe ◽  
Side Lobe Level ◽  
Linear Antenna ◽  
Test Functions ◽  
Linear Antenna Array ◽  
Benchmark Test Functions ◽  
Modified Algorithm

Antenna arrays play an increasingly important role in modern wireless communication systems. However, how to effectively suppress and optimize the side lobe level (SLL) of antenna arrays is critical for communication performance and communication capabilities. To solve the antenna array optimization problem, a new intelligent optimization algorithm called sparrow search algorithm (SSA) and its modification are applied to the electromagnetics and antenna community for the first time in this paper. Firstly, aimed at the shortcomings of SSA, such as being easy to fall into local optimum and limited convergence speed, a novel modified algorithm combining a homogeneous chaotic system, adaptive inertia weight, and improved boundary constraint is proposed. Secondly, three types of benchmark test functions are calculated to verify the effectiveness of the modified algorithm. Then, the element positions and excitation amplitudes of three different design examples of the linear antenna array (LAA) are optimized. The numerical results indicate that, compared with the other six algorithms, the modified algorithm has more advantages in terms of convergence accuracy, convergence speed, and stability, whether it is calculating the benchmark test functions or reducing the maximum SLL of the LAA. Finally, the electromagnetic (EM) simulation results obtained by FEKO also show that it can achieve a satisfactory beam pattern performance in practical arrays.

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.

scholarly journals Position only Antenna Array Synthesis using Normal Distributed Invasive Weed Optimization

2019 ◽  
Vol 9 (2) ◽  
pp. 3277-3280
Keyword(s):  
Antenna Array ◽  
Antenna Arrays ◽  
Stochastic Approach ◽  
Side Lobe ◽  
Linear Antenna ◽  
Invasive Weed Optimization ◽  
Convergence Properties ◽  
Invasive Weed ◽  
Linear Antenna Array ◽  
Antenna Array Synthesis

Nowadays, low-side lobe antenna arrays are used in many communications systems such as satellite, cellular, radar and wireless communications. The antenna array with low side lobe rates should be designed to avoid noisy contact. A new stochastic approach to synthesize a linear antenna array to suppress normal distributed invasive weed optimization (NDIWO) is proposed in this paper synthesize a linear antenna array to suppress the side lobe levels. NDIWO is applied for optimization of the positions of the antenna elements. A 28-element linear array is designed and synthesized by using the proposed and other popular evolutionary algorithms. The acquired radiation designs are gathered with the calculations like particle swarm optimization (PSO) and differential evolution (DE). The numerical results illustrate that the NDIWO optimized antenna array performs superior over PSO and DE optimized arrays in terms of low PSLL and convergence properties.

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