Quantum-Inspired Equilibrium Optimizer for Linear Antenna Array

With the rapid development of communication technology,the problem of antenna array optimization plays a crucial role.Among many types of antennas,line antenna arrays(LAA)are the most commonly applied,but the side lobe level(SLL)reduction is still a challenging problem.In the radiation process of the linear antenna array,the high side lobe level will interfere with the intensity of the antenna target radiation direction.Many conventional methods are ineffective in obtaining the maximumside lobe level in synthesis,and this paper proposed a quantum equilibrium optimizer(QEO)algorithm for line antenna arrays.Firstly,the linear antenna array model consists of an array element arrangement.Array factor(AF)can be expressed as the combination of array excitation amplitude and position in array space.Then,inspired by the powerful computing power of quantum computing,an improved quantum equilibrium optimizer combining quantum coding and quantum rotation gate strategy is proposed.Finally,the proposed quantum equilibrium optimizer is used to optimize the excitation amplitude of the array elements in the linear antenna array model by numerical simulation to minimize the interference of the side lobe level to the main lobe radiation.Six differentmetaheuristic algorithms are used to optimize the excitation amplitude in three different arrays of line antenna arrays,the experimental results indicated that the quantum equilibrium optimizer is more advantageous in obtaining the maximum side lobe level reduction.Compared with other metaheuristic optimization algorithms,the quantum equilibrium optimizer has advantages in terms of convergence speed and accuracy.

New Antenna Array Beamforming Techniques Based on Hybrid Convolution/Genetic Algorithm for 5G and Beyond Communications

Side lobe level reduction(SLL)of antenna arrays significantly enhances the signal-to-interference ratio and improves the quality of service(QOS)in recent and future wireless communication systems starting from 5G up to 7G.Furthermore,it improves the array gain and directivity,increasing the detection range and angular resolution of radar systems.This study proposes two highly efficient SLL reduction techniques.These techniques are based on the hybridization between either the single convolution or the double convolution algorithms and the genetic algorithm(GA)to develop the Conv/GA andDConv/GA,respectively.The convolution process determines the element’s excitations while the GA optimizes the element spacing.For M elements linear antenna array(LAA),the convolution of the excitation coefficients vector by itself provides a new vector of excitations of length N=(2M−1).This new vector is divided into three different sets of excitations including the odd excitations,even excitations,and middle excitations of lengths M,M−1,andM,respectively.When the same element spacing as the original LAA is used,it is noticed that the odd and even excitations provide a much lower SLL than that of the LAA but with amuch wider half-power beamwidth(HPBW).While the middle excitations give the same HPBWas the original LAA with a relatively higher SLL.Tomitigate the increased HPBWof the odd and even excitations,the element spacing is optimized using the GA.Thereby,the synthesized arrays have the same HPBW as the original LAA with a two-fold reduction in the SLL.Furthermore,for extreme SLL reduction,the DConv/GA is introduced.In this technique,the same procedure of the aforementioned Conv/GA technique is performed on the resultant even and odd excitation vectors.It provides a relatively wider HPBWthan the original LAA with about quad-fold reduction in the SLL.

Effects of Spatial Characteristics on Smart Antenna System with Uniform Linear Antenna Array

The effect of the spatial characteristics of antenna array on smart antenna systems can not be neglected. In the paper, the relation between spatial correlation and inter-antenna distance, impinging angle, angle spread is first investigated. With the same beam forming algorithm, we simulate the performance of smart antenna system with different Angle Spread （AS） values on the conditions of ideal and real Angle of Arrival （AOA） estimation. The results show that with the ideal AOA estimation, the AOA is enough accurate to guarantee that the system only has little performance degradation even in the case of 20 degreee AS value while the real AOA estimation influenced by channel environment degrades the performance very obviously, up to about 7 dB.

Length minimization of uniform linear antenna array for millimeter wave communications with maximum capacity

For uniform linear antenna array （ULA） based millimeter wave communications, the maximum capacity can be achieved by the optimal antenna separation product （ASP）. However, due to the practical size limitation, it is necessary to decrease the ULA length. In this paper, an optimization problem is formulated to minimize the ULA length for millimeter wave communications with maximum capacity. We decompose the problem into two subproblems： length selection optimization and orientation deployment optimization. The optimal length selection can be obtained when the transmit and receive ULAs have equal length. By using the property of trigonometric function, we derive the optimal orientation deployment and study the influence of orientation deviation on ULA length. Simulation results are presented to validate the analyses.