Maximum Side Lobe Level Reduction Research Articles

Thinned Smart Antenna of a Semi-circular Dipole Array for Massive MIMO Systems

Massive MIMO (multiple-input multiple-output) is a multi-user MIMO technology that can provide high-speed multimedia services in 5G wireless networks using sub-6 GHz and millimeter wave bands. The massive MIMO (MMIMO) installs array antennas in the base stations, using hundreds of transceivers with other RF modules. One of the drawbacks of the MMIMO system is its huge power consumption, and the beamforming network with RF modules for a large number of antennas is the main contributor to the power consumption. In this paper, a novel beamforming method is proposed for the low power consumption of an MMIMO system. The proposed thinned smart antenna (TSA) of a semi-circular array produces a secure beam toward the user’s terminal with reduced interference. By thinning the antenna array, some of the antenna elements are kept off, resulting in less power consumption, while the array pattern remains the same as a fully populated array with a reduced side lobe level (SLL). The sub-6 GHz band of 5 GHz is used for the design of thinned array antennas. The genetic algorithm (GA) is used to determine the array sequence in thinning, and the adaptive signal processing algorithms least mean square (LMS), recursive least square (RLS), and sample matrix inversion (SMI) are used for the beamforming of the TSA, and the corresponding algorithms are GA-LMS, GA-RLS, and GA-SMI. The power saving of 40% to 55% is achieved using TSA. The maximum SLL reductions of 13 dB, 12 dB, and 14 dB are achieved for TSA using GA-LMS, GA-RLS, and GA-SMI algorithms, respectively.

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 maximum side 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 different metaheuristic 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.

Novel Design Techniques for the Fermat Spiral in Antenna Arrays, for Maximum SLL Reduction.

This paper presents novel design techniques for the Fermat spiral, considering a maximum side lobe level (SLL) reduction. The array system based on a Fermat spiral configuration considers techniques based on uniform and non-uniform amplitude excitation. The cases of uniform amplitude excitation are the golden angle and the optimization of the angular separations. The cases of non-uniform amplitude excitations consider a raised cosine distribution and the optimization of the amplitude excitations through the Fermat spiral array. In this study, the method of genetic algorithms (GA) was used in the cases to find the values of the angular separations and the amplitude excitations of the Fermat spiral array. A performance evaluation was conducted for all these design cases, considering the Fermat spiral geometry. These design cases were validated using electromagnetic simulation to take mutual coupling into account and consider the effect of the antenna element pattern in each proposed design case.

Optimization of Coupled Periodic Antenna Using Genetic Algorithm with Floquet Modal Analysis and MoM-GEC

In this paper Genetic Algorithm has been integrated with Fouquet modal analysis to optimize radiation pattern of coupled periodic antenna. Floquet analysis is used with MoM-GEC (Moment-Generalized Equivalent Circuit) method to study a finite periodic array with uniform amplitude and linear phase distribution. This method is very advantageous for studying large antenna array since it considerably reduces the computation time and the number of operations. In this way, Genetic algorithm is introduced and combined with Floquet analysis to optimize the radiation pattern distribution of this coupled periodic antenna. The goal of the optimization is to provide a better radiation characteristic for the coupled periodic antenna with maximum side lobe level reduction.

Optimal Design of Linear Antenna Arrays of Dipole Elements Using Flower Pollination Algorithm

ABSTRACTThis paper describes the synthesis of the radiation characteristics of linear antenna arrays of dipole elements using a nature inspired algorithm called flower pollination algorithm (FPA), which is applied as an optimization algorithm. In FPA, element's current excitation and the inter-element spacing are used as the optimizing variables to obtain better radiation characteristics of the antenna arrays. The advent is illuminated by 12-, 16-, and 20-elements linear arrays of dipole elements. The simulation results show the influence of this approach on the maximum side lobe level reduction with fixed first null beam width. The obtained results are validated in a practical simulation environment, called computer simulation technology-microwave studio software.

Comparative Study of Circular and Hexagonal Antenna Array Synthesis Using Improved Particle Swarm Optimization

This paper describes the comparison of the performance of Circular array (CA) and Hexagonal Array (HA) of uniformly excited isotropic antennas which can generate directive beam with minimum relative Side Lobe Level (SLL). The Improved Particle Swarm Optimization (IPSO) method, which represents a novel approach for optimization problems in electromagnetic, is used in the optimization process. Two examples has been presented and solved. In first example, the IPSO is used to determine an optimal set of ‘ON-OFF’ elements in an 12 element thinned array, and in second example, IPSO is used to determine an optimal set of amplitude distributions in an 18 element array that provide a radiation pattern with maximum SLL reduction. This paper is basically concerned with the comparison of the performance of thinned CA and HA in terms of SLL by fixing the other array design variable. Numerical results for synthesizing two different array geometries demonstrated the superiority of Hexagonal Array over the Circular Array for both the examples.

Certain investigations on the reduction of side lobe level of an uniform linear antenna array using biogeography based optimization technique with sinusoidal migration model and simplified-BBO

In this paper, we propose biogeography based optimization technique, with linear and sinusoidal migration models and simplified biogeography based optimization (S-BBO), for uniformly spaced linear antenna array synthesis to maximize the reduction of side lobe level (SLL). This paper explores biogeography theory. It generalizes two migration models in BBO namely, linear migration model and sinusoidal migration model. The performance of SLL reduction in ULA is investigated. Our performance study shows that among the two, sinusoidal migration model is a promising candidate for optimization. In our work, simplified – BBO algorithm is also deployed. This determines an optimum set value for amplitude excitations of antenna array elements that generate a radiation pattern with maximum side lobe level reduction. Our detailed investigation also shows that sinusoidal migration model of BBO performs better compared to the other evolutionary algorithms discussed in this paper.

Synthesis of a Linear Antenna Array for Maximum Side-lobe Level Reduction

are number of Techniques used to reduce Side Lobe Level (SLL) of antenna arrays to save power and improve Quality of Service (QoS) by ensuring maximum radiation in desired direction, several methods are available in literature. It is a well known fact that when an attempt is made to reduce the first sidelobe level of an antenna array, the beamwidth increases. However, in the present work, an array for a specified first side lobe level of -35dB was synthesized using Dolph Chebyshev method. A real-value Genetic Algorithm (RGA) was also used to optimize the current excitations. The weighting vectors are compared. Using these vectors, patterns are generated for arrays of different elements. The resultant patterns are compared and the result shows greater improvement in the SLL reduction from the RGA method without deteriorating the main beamwidth. Keywordslobe level, Quality of Service, beamwidth, Dolph Chebyshev, and Real-Value Genetic Algorithm 1. INTRODUCTION antenna array is a group of identical antenna elements

Design of Linear and Elliptical Antenna Arrays Using Biogeography Based Optimization

In this paper, the problem of designing linear and elliptical antenna arrays for specific radiation properties is dealt with. The biogeography-based optimization (BBO) method, which represents a new evolutionary algorithm, is used in the optimization process. BBO is used to minimize the maximum side lobe level (SLL) and null control for isotropic linear antenna arrays by optimizing different array parameters (position, amplitude, and phase). Similarly, for elliptical antenna array, four optimization techniques (BBO, genetic algorithm, self-adaptive differential evolution, and sequential quadratic programming) are used to determine an optimum set of weights that provide a radiation pattern with maximum SLL reduction with the constraint of a fixed major lobe beam width. The obtained results show the effectiveness of BBO compared to other well-known optimization methods.

Elliptical Antenna Array Pattern Synthesis with Fixed Side Lobe Level and Suitable Main Lobe Beam width by Genetic Algorithm

In this paper, the design of uniform elliptical array (UEA) with optimum side lobe level reduction is presented. Multi-lobe pattern and adaptive nulling of the pattern is achieved by the control of the antenna elements phases in different states. This method is based on genetic algorithm (GA). The method of genetic algorithm is used to determine an optimum set of array factor cost that provide a radiation pattern with maximum side lobe level reduction with constraint of a suitable main lobe beamwidth. The results show that synthesis of the uniform elliptical antenna array by using GA method provide a side lobe level reduction and main lobe beamwidth better than circular antenna array obtained by using IWO (Invasive Weeds Optimization) and also optimized elliptical antenna array by using EPL (The Excitations Of Elements Phases at Eccentricity Low Level).

Optimized radii and excitations with concentric circular antenna array for maximum sidelobe level reduction using wavelet mutation based particle swarm optimization techniques

In this paper, a Particle Swarm Optimization with Constriction Factor and Inertia Weight Approach with Wavelet Mutation (PSOCFIWA-WM) is applied to the process of synthesizing three-ring Concentric Circular Antenna Arrays (CCAA) without and with central element feeding, focused on maximum sidelobe level reductions. Sidelobe level (SLL) is a critical radiation pattern parameter in the task of reducing background noise and interference in the most recent wireless communication systems. To improve the radiation pattern with maximum SLL reduction, an optimum set of antenna element parameters as excitation weights and radii of the rings are to be developed. The extensive computational results show that the method of PSOCFIWA-WM provides a maximum sidelobe level reduction of 96.06% with respect to the uniformly excited case for the particular CCAA containing 4, 6, and 8 numbers of elements in the three successive rings along with central element feeding.

Side lobe reduction of a concentric circular antenna array using genetic algorithm

A concentric circular antenna array (CCAA) consists of elements positioned on the periphery of imaginary circles on a plane having a common centre and different radii. The simplest way to feed the elements of such an array is to use uniform excitation. However, with a non-uniform excitation profile, considerable reduction of the side lobe level (SLL) may be achieved at the cost of the added complexity. The difference of SLLs (with respect to the uniform excitation case) becomes even more prominent when the beamwidth of the antenna needs to be kept fixed. In this paper, we formulate the task of designing a non-uniformly excited CCAA as a constrained optimization problem and use genetic algorithm (GA) to solve the same. The goal is to determine an optimum set of weights for antenna elements which provides a radiation pattern with maximum SLL reduction with the constraint of a fixed beamwidth.

LINEAR ARRAY SYNTHESIS USING BIOGEOGRAPHY BASED OPTIMIZATION

This paper presents a novel optimization technique biogeography based optimization (BBO) for antenna array synthesis. BBO is a relatively new evolutionary global optimization technique based on the science of biogeography. It is capable of solving linear and non-linear problems. In this paper, BBO algorithm is used to determine an optimum set of amplitudes of antenna elements that provide a radiation pattern with maximum side lobe level reduction and/or null placement in the specifled directions. The results obtained show the efiectiveness of the BBO algorithm, and they are better than previous published results.

Design of scannable linear arrays with amplitude and phase optimisation for maximum side lobe level reduction

The design problem of scannable linear arrays is dealt with. This design of scannable linear arrays considers the optimisation of the amplitude and phase excitation across the antenna elements by using the well-known method of genetic algorithms (GAs). Simulation results for scannable linear arrays with the amplitude and phase excitation optimised by the GA are provided. Furthermore, in order to discover which design case could provide a better performance in side lobe level, a comparative analysis of the performance of the optimised design case with a conventional phased linear array is undertaken.