Uniform and Concentric Circular Antenna Arrays Synthesis for Smart Antenna Systems Using Artificial Neural Network Algorithm

Abstract

Abstract-Recently, researchers were interested in neural algorithms for optimization problems for several communication systems. This paper shows a novel algorithm based on neural technique presented to enhance the performance analysis of beam-forming in smart antenna technology using N elements for Uniform Circular Array (UCA) and Concentric Circular Array (CCA) geometries. To demonstrate the effectiveness and reliability of the proposed approach, simulation results are carried out in MATLAB. The radiators are considered isotropic, and hence mutual coupling effects are ignored. The proposed array shows a considerable improvement against the existing structures in terms of 3-D scanning, size, directivity, HPBW and SLL reduction. The results show that multilayer feed-forward neural networks are robust and can solve complex antenna problems. However, artificial neural network (ANN) is able to generate very fast the results of synthesis by using generalization with early stopping method. Important gain in the running time and memory used is obtained using this latter method for improving generalization (called early stopping). To validate this work, several examples are shown.

Effects of Narrow Beam Phased Antenna Arrays over the Radio Channel Metrics, Doppler Power Spectrum, and Coherence Time, in a Context of 5G Frequency Bands

“…The number of elements required for each antenna array, according to its geometry, are follows: (1) planar (PA) of the 8x8 and 16x16 elements, respectively; (2) circular (CA) of 21 and 47 elements; and (3) 42 circular concentric rings (CR) (with three rings) and 196 (with seven rings) elements. The design and model of each array geometry were carried out by computing the array factor; PA [28][29][30][31][32], CA [28][29][30][31]33], CR [34][35][36][37][38].…”

Pengaruh Elemen Sentral Pada Susunan Antena Sirkular Untuk Sistem Teleskop Radio Transit

“…Side lobe tersebut muncul akibat grating lobe pada pola susunan (array pattern) yang mulai muncul ketika dua buah elemen pada susunan antena terpisah pada jarak yang melebihi setengah panjang gelombang [9]. Berbagai penelitian telah dilakukan untuk menekan intensitas side lobe tersebut, antara lain penggunaan algoritma Flower Pollination [6], teknik Cat Swarm Optimization [10], teknik Particle Swarm Optimization dengan skala penyempitan dan pendekatan berat inersia [11] dan algoritma artificial neural network [12].…”

Radiation Pattern Synthesis of the Coupled Almost Periodic Antenna Arrays Using Artificial Neural Network ANN Model

“…In general, smart antenna arrays involve intelligent systems including genetic algorithms and neural networks to synthesize the radiation pattern [2,3]. Many research papers are proving that genetic algorithm (GA) is used basically for sidelobe reduction in antenna pattern synthesis [15,18]. As well, artificial neural networks (ANN) have been employed in various purposes such as pattern recognition systems, and have been taken into use for input-output mapping, system identification, adaptive prediction, etc..... Consequently, the present work is centered on the neural network technique that will be implemented for the synthesis of almost periodic network models, pointing out their most prominent features and distinctive characteristics [17,24,25].…”