Korany Ragab Mahmoud

A Comparison Between Circular and Hexagonal Array Geometries for Smart Antenna Systems Using Particle Swarm Optimization Algorithm

In this paper, circular and hexagonal array geometries for smart antenna applications are compared. Uniform circular (UCA) and hexagonal arrays (UHA) with 18 half-wave dipole elements are examined; also planar (2 concentric rings of radiators) uniform circular (PUCA) and hexagonal arrays (PUHA) are considered. The effect of rotating the outer ring of the PUCA is studied. In our analysis, the method of moments is used to compute the response of the uniform circular and hexagonal dipole arrays in a mutual coupling environment. The particle swarm optimization (PSO) algorithm is used to optimize the complex excitations, amplitudes and phases, of the adaptive arrays elements for beamforming.

DESIGN OPTIMIZATION OF A BOW-TIE ANTENNA FOR 2.45 GHz RFID READERS USING A HYBRID BSO- NM ALGORITHM

Recently the Bacterial foraging optimization algorithm (BFA) has attracted a lot of attention as a high-performance optimizer. This paper presents a hybrid approach involving Bacterial Swarm Optimization (BSO) and Nelder-Mead (NM) algorithm. The proposed algorithm is used to design a bow-tie antenna for 2.45GHz Radio Frequency Identiflcation (RFID) readers. The antenna is analyzed completely using Method of Moments (MoM), then the MoM code is coupled with the BSO-NM algorithm to optimize the antenna. The simulated antenna and the optimization algorithm programs were implemented using MATLAB version 7.4. To verify the validity of numerical simulations, the results are compared with those obtained using Feko Software Suite 5.3.

INVESTIGATING THE INTERACTION BETWEEN A HUMAN HEAD AND A SMART HANDSET FOR 4G MOBILE COMMUNICATION SYSTEMS

In this paper we evaluate the potential of a 5-element monopole array incorporated into a handheld device for beamforming in the 5.0-GHz band. The geometry of the handset consists of a 5-element array: four elements located at the handset corners and the fifth-element located at the center. Also, the interaction of the antenna array, mounted on a mobile handset, with a human head phantom is investigated. Firstly, the spatial peak specific absorption rate (SAR) values of 5-element array antennas for mobile handsets in the vicinity of a spherical phantom of a human head are evaluated numerically as a function of the distance between the handset and the head phantom for two different scenarios. Next, the effect of the human head on the handset radiation pattern is studied. The effect of different handset positions on the radiation pattern is also considered. The particle swarm optimization (PSO) algorithm is used to optimize the complex excitations of the adaptive arrays elements in a mutual coupling environment for beamforming synthesis. All numerical simulations are performed using the FEKO Suite 5.3

AN INTERACTION STUDY BETWEEN PIFAS HANDSET ANTENNA AND A HUMAN HAND-HEAD IN PERSONAL COMMUNICATIONS

Abstract—In this paper, the interaction of a planar inverted-F antennas array, mounted on a mobile handset, with a human hand-head phantom is investigated in the 1.9GHz band. The hybrid approach involving the particle swarm optimization (PSO) and Nelder-Mead (NM) algorithm is considered to optimize the complex excitations of the adaptive array elements in a mutual coupling environment for different beamforming synthesis. Firstly, the effect of the human handhead on the handset radiation characteristics is studied. Then, the spatial-peak specific absorption rate (SAR) values of 2and 4-element PIFA arrays for mobile handset in the vicinity of a human handhead are evaluated numerically for different scenarios. The antenna is analyzed completely using finite difference time domain (FDTD) method while the interaction is performed using the CST Microwave Studio software.

MPSO-MOM: A Hybrid Modified Particle Swarm Optimization and Method of Moment Algorithm for Smart Antenna Synthesis

Abstract In this article, a modified version of particle swarm optimization (MPSO) and the method of moment (MOM) are combined to achieve the beamforming objective of a practical smart antenna array. The hybrid approach (MPSO–MOM) is illustrated by application to a planar uniform circular array (PUCA) with 30 elements of half-wave dipoles. The array feeding is optimized by MPSO, and the fitness function is evaluated by MOM simulations. The MOM is used to calculate the response of the array in a mutual coupling environment. The performance of the adaptive array using discrete (quantized) feedings is studied. Also in this article, the convergence capability of the MPSO is compared with that of the classical particle swarm optimization and other recent evolutionary-based algorithms using benchmark examples and a linear array synthesis problem.

Parallel Implementation of Hybrid Gsa-Nm Algorithm for Adaptive Beam-Forming Applications

Recently researchers have great interest in using multi-core processors for applications requiring intensive parallel computing. In this paper, an approach for the implementation of hybrid parallel Gravitational Search Algorithm (GSA) and Nelder-Mead (NM) algorithm using open Multi- Processing (OPEN-MP) on multi-core processors is proposed for beam-forming applications. The proposed parallel GSA-NM algorithm is used to optimize the complex excitations, amplitudes and phases, of the adaptive array elements to synthesize the array beam-pattern. The array consists of 24- elements uniformly distributed in a circular conflguration. To measure the performance of the proposed approach, the results are compared with those obtained using parallel hybrid CFO-NM, and PSO-NM Algorithms.

Design of Compact Double-Layer Microwave Absorber for X-Ku Bands Using Genetic Algorithm

In this paper, an efficient lightweight double-layer microwave absorber with impedance- matching structure at X-Ku bands was designed, optimized and implemented. First, genetic algorithm (GA) was considered to optimize the thicknesses and material properties for better absorption of the incident electromagnetic wave and reduction of radar cross section (RCS). Next, with the aid of the obtained dielectric and magnetic properties, the microwave absorber was fabricated from magneto- dielectric composite materials besides a natural rubber. Finally, the analytical and numerical results were compared with the measurements to check the validity of the design. Experiments showed that the reflection coefficient for each layer backed with a metallic sheet was insufficient; however, for the double layer absorber, the reflectivity measurement values reached up to −28 dB in the case of normal incidence and −17 dB for oblique incidence.

Design Bluetooth and Notched-UWB E-Shape Antenna Using Optimization Techniques

In this article, an optimized E-shaped patch antenna for Bluetooth (2.4{2.484GHz) and UWB (3.1{10.6GHz) applications with WLAN (5.15{5.825GHz) band-notched characteristics is proposed. The dimensions of the E-shaped antenna structure in addition to the position of the slotted C-shape in the ground plane are optimized using recent optimization techniques such as Modifled Particle Swarm Optimization (MPSO), Bacterial Swarm Optimization (BSO), and Central Force Optimization (CFO). The optimization algorithms were implemented using MATLAB-software and linked to the CST Microwave Studio to simulate the antenna. Next, the efiects of the Laptop structure on the antenna radiation characteristics are considered. Finally, the antenna structures are simulated by the flnite difierence time domain method (FDTD) to validate the results. The measured results exhibit good agreement with the simulation from CST and the Finite Difierence Time Domain (FDTD) program written with matlab.

CFO Parallel Implementation on GPU for Adaptive Beam-forming Applications

The scientific community is still interested in heuristic techniques and optimization algorithms that could be applied in complex problems such as the antenna adaptive beam forming problem. This paper presents an empirical study of solving the problem of antenna adaptive beam forming using Central Force Optimization (CFO) algorithm. The algorithm implemented using Compute Unified Device Architecture (CUDA) then applied on a graphics processing unit (GPU). CFO is well known alternatives for global optimization based on a nature-inspired Heuristic. Extensive experimentations were applied to compare their performance through a number of case studies. CFO has a higher computational complexity but it gives good results. The experimentations showed that the resulting beam-pattern optimized by the CFO required a large processing time which is not acceptable for an on line applications. Hence, the demand for a parallel solution that accelerates these computations is considered. Therefore, a parallel version of CFO is proposed and implemented using (CUDA) then applied on a (GPU). The comparison is presented to show how the parallel version of the CFO outperforms the sequential one, thus an online procedure is available for time-critical applications of the adaptive beamforming.