Abstract
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.
Highlights
The latest development trend of wireless communication systems is to realize the antenna array system with strong directivity and maneuverability, so that it can radiate and receive energy to the maximum extent in a specific direction and reduce the waste of energy by suppressing the side lobe level (SLL) in noninteresting directions [1]
In order to further improve the performance of the algorithm, this paper proposes a new modified algorithm based on chaotic adaptive inertia weight and improved boundary constraint
The numerical results of this paper indicate that the modified algorithm shows promise as an effective method in solving the global optimization problems
Summary
The latest development trend of wireless communication systems is to realize the antenna array system with strong directivity and maneuverability, so that it can radiate and receive energy to the maximum extent in a specific direction and reduce the waste of energy by suppressing the SLL in noninteresting directions [1]. According to the pattern multiplication theorem, the pattern of an antenna array can be obtained by multiplying the element pattern by the array factor. Excitation amplitude, and phase of array factor, the antenna array can have the characteristics of high gain, narrow beam, low SLL, and easy electrical scanning [2]. In the field of scientific research and engineering practice, most of the problems encountered can be attributed to solving optimization problems, and the design and optimization of the antenna array are no exception [3]. With its unique advantages in solving large-scale, nonlinear, and other complex optimization problems, the design and optimization technology of antenna arrays based on an intelligent optimization algorithm has always been a research hotspot in the field of EM optimization [4]
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