Comparison of Evolutionary Optimization Algorithms for FM-TV Broadcasting Antenna Array Null Filling

Broadcasting antenna array null filling is a very challenging problem for antenna design optimization. This paper compares five antenna design optimization algorithms (Differential Evolution, Particle Swarm, Taguchi, Invasive Weed, Adaptive Invasive Weed) as solutions to the antenna array null filling problem. The algorithms compared are evolutionary algorithms which use mechanisms inspired by biological evolution, such as reproduction, mutation, recombination, and selection. The focus of the comparison is given to the algorithm with the best results, nevertheless, it becomes obvious that the algorithm which produces the best fitness (Invasive Weed Optimization) requires very substantial computational resources due to its random search nature

Pattern Synthesis of Dual-band Shared Aperture Interleaved Linear Antenna Arrays

This paper presents an approach to improve the efficiency of an array aperture by interleaving two different arrays in the same aperture area. Two sub-arrays working at different frequencies are interleaved in the same linear aperture area. The available aperture area is efficiently used. The element positions of antenna array are optimized by using Invasive Weed Optimization (IWO) to reduce the peak side lobe level (PSLL) of the radiation pattern. To overcome the shortness of traditional methods which can only fulfill the design of shared aperture antenna array working at the same frequency, this method can achieve the design of dual-band antenna array with wide working frequency range. Simulation results show that the proposed method is feasible and efficient in the synthesis of dual-band shared aperture antenna array

IWO-based Synthesis of Log-Periodic Dipole Array

The Invasive Weed Optimization (IWO) is an effective evolutionary and recently developed method. Due to its better performance in comparison to other well-known optimization methods, IWO has been chosen to solve many complex non-linear problems in telecommunications and electromagnetics. In the present study, the IWO is applied to optimize the geometry of a realistic log-periodic dipole array (LPDA) that operates in the frequency range 800-3300 MHz and therefore is suitable for signal reception from several RF services. The optimization is applied under specific requirements, concerning the standing wave ratio, the forward gain, the gain flatness and the side lobe level, over a wide frequency range. The optimization variables are the lengths and the radii of the dipoles, the distances between them, and the characteristic impedance of the transmission line that connects the dipoles. The optimized LPDA seems to be superior compared to the antenna derived from the practical design procedure

Optimal Wideband LPDA Design for Efficient Multimedia Content Delivery over Emerging Mobile Computing Systems

An optimal synthesis of a wideband Log-Periodic Dipole Array (LPDA) is introduced in the present study. The LPDA optimization is performed under several requirements concerning the standing wave ratio, the forward gain, the gain flatness, the front-to-back ratio and the side lobe level, over a wide frequency range. The LPDA geometry that complies with the above requirements is suitable for efficient multimedia content delivery. The optimization process is accomplished by applying a recently introduced method called Invasive Weed Optimization (IWO). The method has already been compared to other evolutionary methods and has shown superiority in solving complex non-linear problems in telecommunications and electromagnetics. In the present study, the IWO method has been chosen to optimize an LPDA for operation in the frequency range 800-3300 MHz. Due to its excellent performance, the LPDA can effectively be used for multimedia content reception over future mobile computing systems

Pattern Synthesis of Planar Nonuniform Circular Antenna Arrays Using a Chaotic Adaptive Invasive Weed Optimization Algorithm

A novel invasive weed optimization (IWO) variant called chaotic adaptive invasive weed optimization (CAIWO) is proposed and applied for the optimization of nonuniform circular antenna arrays. A chaotic search method has been combined into the modified IWO with adaptive dispersion, where the seeds produced by a weed are dispersed in the search space with standard deviation specified by the fitness value of the weed. To evaluate the performance of CAIWO, several representative benchmark functions are minimized using various optimization algorithms. Numerical results demonstrate that the proposed approach improves the performance of the algorithm significantly, in terms of both the convergence speed and exploration ability. Moreover, the scheme of CAIWO is employed to find out an optimal set of weights and antenna element separation to obtain a radiation pattern with maximum side-lobe level (SLL) reduction with different numbers of antenna element under two cases with different purposes. The design results obtained by CAIWO have comfortably outperformed the published results obtained by other state-of-the-art metaheuristics in a statistically meaningful way

Characteristics of different focusing antennas in the near field region

Focusing antennas are of interest in many application including microwave wireless power transmission, remote (non-contact) sensing, and medical applications. Different kinds of antennas such as array antennas, reflector antennas and Fresnel zone plate (FZP) antennas have been used for these applications. Here, first, a new scheme in designing focused array antennas with desired sidelobe levels (SLLs) in the near field region is presented. The performance of the large focused array antennas is predicted based on the knowledge of the mutual admittances of a smaller array. The effects of various focal distances on the near field pattern of these antennas are investigated. Then, electric field pattern characteristics of the focused Fresnel zone plate lens antennas in the near-field region are presented. The FZP antenna fed by a circular horn is implemented and the effects of various focal lengths on the near field pattern of this antenna are examined. It is shown that the maximum field intensity occurs closer to the antenna aperture than to the focal point and this displacement increases as the focal point moves away from the antenna aperture. The focusing properties of ultra-wideband (UWB) array antennas are also presented. Large current radiator (LCR) antennas are modeled by replacing the antenna with a set of infinitesimal dipoles producing the same near field of the antenna. LCR antenna arrays are used to provide high concentration of microwave power into a small region. It is shown that the defocusing effect occurs in pulse radiating antennas as well. Invasive weed optimization (IWO), a new optimization algorithm, is also employed to optimize the pulsed array antenna. In the attempt of optimizing the focused arrays, a new scenario for designing thinned array antennas using this optimization method is introduced. It is shown that by using this method, the number of elements in the array can be optimized, which yields a more efficient pattern with less number of elements. By applying this new optimization method to UWB arrays, the peak power delivered to a localized region can be increased

Reconfigurable aperiodic array synthesis by Compressive Sensing

Aperiodic arrays represent an attractive technology for applications requiring multiple pencil beams or contour beams, such as in radars, satellite communication and mw-sensor systems. These antennas are typically designed to either produce high-directivity beams over a given scan range or a single beam with a specified complex shape. In this manuscript we present a CS approach for the synthesis of a single aperiodic array layout capable of radiating multiple beams with different shapes The approach aims at designing reconfigurable arrays with least number of elements as well as the optimal excitation set for each of the desired beams. Preliminary results for an array providing both pencil and a flattop coverage are presented

The optimal synthesis of scanned linear antenna arrays

In this paper, symmetric scanned linear antenna arrays are synthesized, in order to minimize the side lobe level of the radiation pattern. The feeding current amplitudes are considered as the optimization parameters. Newly proposed optimization algorithms are presented to achieve our target; Antlion Optimization (ALO) and a new hybrid algorithm. Three different examples are illustrated in this paper; 20, 26 and 30 elements scanned linear antenna array. The obtained results prove the effectiveness and the ability of the proposed algorithms to outperform and compete other algorithms like Symbiotic Organisms Search (SOS) and Firefly Algorithm (FA)

Nature-inspired Cuckoo Search Algorithm for Side Lobe Suppression in a Symmetric Linear Antenna Array

In this paper, we proposed a newly modified cuckoo search (MCS) algorithm integrated with the Roulette wheel selection operator and the inertia weight controlling the search ability towards synthesizing symmetric linear array geometry with minimum side lobe level (SLL) and/or nulls control. The basic cuckoo search (CS) algorithm is primarily based on the natural obligate brood parasitic behavior of some cuckoo species in combination with the Levy flight behavior of some birds and fruit flies. The CS metaheuristic approach is straightforward and capable of solving effectively general N-dimensional, linear and nonlinear optimization problems. The array geometry synthesis is first formulated as an optimization problem with the goal of SLL suppression and/or null prescribed placement in certain directions, and then solved by the newly MCS algorithm for the optimum element or isotropic radiator locations in the azimuth-plane or xy-plane. The study also focuses on the four internal parameters of MCS algorithm specifically on their implicit effects in the array synthesis. The optimal inter-element spacing solutions obtained by the MCS-optimizer are validated through comparisons with the standard CS-optimizer and the conventional array within the uniform and the Dolph-Chebyshev envelope patterns using MATLABTM. Finally, we also compared the fine-tuned MCS algorithm with two popular evolutionary algorithm (EA) techniques include particle swarm optimization (PSO) and genetic algorithms (GA)