Katherine Siakavara

Application of a Comprehensive Learning Particle Swarm Optimizer to Unequally Spaced Linear Array Synthesis With Sidelobe Level Suppression and Null Control

We present unequally spaced linear array synthesis with sidelobe suppression under constraints to beamwidth and null control using a design technique based on a Comprehensive Learning Particle Swarm Optimizer (CLPSO). CLPSO utilizes a new learning strategy that achieves the goal to accelerate the convergence of the classical PSO. Numerical examples are compared to the existing array designs in the literature and to those found by the other evolutionary algorithms. The synthesis examples that are presented show that the CLPSO algorithm outperforms the common PSO algorithms and a real-coded genetic algorithm (GA).

NOVEL FRACTAL ANTENNA ARRAYS FOR SATELLITE NETWORKS: CIRCULAR RING SIERPINSKI CARPET ARRAYS OPTIMIZED BY GENETIC ALGORITHMS

A novel fractal antenna-array type is proposed. The design is based on the Sierpinski rectangular carpet concept. However, the generator is a circular ring area, fllled with radiating elements, so the higher stages of the fractal development produce large arrays of circular rings which, besides the high directivity, have the advantage of the almost uniform azimuthal radiation pattern, attribute that many applications require. The introduced arrays can operate as direct radiating multi-beam phased arrays and meet the requirements of satellite communications links: high End of Coverage (EOC) directivity, low Side Lobe Level (SLL) and high Career to Interference ratio (C=I). These operational indices were further optimized by a synthesized multi-objective and multi-dimensional Genetic Algorithm (GA) which, additionally, gave arrays no more than 120 elements.

On the Direction of Arrival (DoA) Estimation for a Switched-Beam Antenna System Using Neural Networks

A generic direction of arrival (DoA) estimation methodology is presented that is based on neural networks (NNs) and designed for a switched-beam system (SBS). The method incorporates the benefits of NNs and SBSs to achieve DoA estimation in a less complex and expensive way compared to the corresponding widely known super resolution algorithms. The proposed technique is step-by-step developed and thoroughly studied and explained, especially in terms of the beam pattern structure and the neuro-computational procedures. Emphasis is given on the direct sequence code division multiple access (DS-CDMA) applications, and particularly the Universal Mobile Telecommunication System (UMTS). Extensive simulations are realized for each step of the method, demonstrating its performance. It is shown that a properly trained NN can accurately find the signal of interest (SoI) angle of arrival at the presence of a varying number of mobile users and a varying SoI to interference ratio. The proposed NN-SBS DoA estimation method can be applied to current cellular communications base stations, promoting the wider use of smart antenna beamforming.

Sparse Linear Array Synthesis With Multiple Constraints Using Differential Evolution With Strategy Adaptation

This letter addresses the problem of designing sparse linear arrays with multiple constraints. The constraints could include the minimum and maximum distance between two adjacent elements, the total array length, the sidelobe level suppression in specified angular intervals, the main-lobe beamwidth, and the predefined number of elements. Our design method is based on differential evolution (DE) with strategy adaptation. We apply a DE algorithm (SaDE) that uses previous experience in both trial vector generation strategies and control parameter tuning. Design cases found in the literature are compared to those found by SaDE and other DE algorithms. The results show that fewer objective-function evaluations are required than those reported in the literature to obtain better designs. SaDE also outperforms the other DE algorithms in terms of statistical results.

A Multi-Objective Approach to Subarrayed Linear Antenna Arrays Design Based on Memetic Differential Evolution

In this paper we present a multi-objective optimization approach to subarrayed linear antenna arrays design. We define this problem as a bi-objective one. We consider two objective functions for directivity maximization and sidelobe level minimization. Memetic algorithms (MAs) are hybrid algorithms that combine the benefits of a global search Evolutionary Algorithm (EA) with a local search method. In this paper, we introduce a new memetic multi-objective evolutionary algorithm namely the memetic generalized differential evolution (MGDE3). This algorithm is a memetic extension of the popular generalized differential evolution (GDE3) algorithm. Another popular MOEA is the nondominated sorting genetic algorithm-II (NSGA-II). MGDE3, GDE3 and NSGA-II are applied to the synthesis of uniform and nonuniform subarrayed linear arrays, providing an extensive set of solutions for each design case. Depending on the desired array characteristics, the designer can select the most suitable solution. The results of the proposed method are compared with those reported in the literature, indicating the advantages and applicability of the multi-objective approach.

Pareto Optimal Yagi-Uda Antenna Design Using Multi-Objective Differential Evolution

Antenna design problems often require the optimization of several con∞icting objectives such as gain maximization, sidelobe level (SLL) reduction and input impedance matching. Multi- objective Evolutionary Algorithms (MOEAs) are suitable optimization techniques for solving such problems. An e-cient algorithm is Generalized Difierential Evolution (GDE3), which is a multi-objective extension of Difierential Evolution (DE). The GDE3 algorithm can be applied to global optimization of any engineering problem with an arbitrary number of objective and constraint functions. Another popular MOEA is Nondominated Sorting Genetic Algorithm- II (NSGA-II). Both GDE3 and NSGA-II are applied to Yagi-Uda antenna design under specifled constraints. The numerical solver used for antenna parameters calculations is SuperNEC, an object-oriented version of the numerical electromagnetic code (NEC-2). Three difierent Yagi-Uda antenna designs are considered and optimized. Pareto fronts are produced for both algorithms. The results indicate the advantages of this approach and the applicability of this design method.

Aperiodic Array Layout Optimization by the Constraint Relaxation Approach

An optimization procedure for the layout assessment of electrically large but finite planar arrays is presented. The synthesis takes into account the desired directivity pattern that is prescribed employing bound constraints. Moreover, the size of the radiators is taken into account, which results in a hard nonoverlapping, between the elements, constraint. The latter should not be violated if we want the attained solution not only to obey the far-field mask, but also to be physically realizable. As stated, the optimization problem is twofold. An antenna design is associated with a packing problem. In order to take the constraints on the layout into account and solve the whole problem, we propose the constraint relaxation approach, which is equipped with a packing algorithm. Our study is applied to various initial geometries, and the resulting arrays appear to comply with the desired pattern and the nonoverlapping constraint. Several examples for different cases including symmetric arrays and a study on maximally sparse arrays are presented, which show the applicability and merit of the method.

Novel Spiral Antenna Design Using Artificial Bee Colony Optimization for UHF RFID Applications

In this letter, a new planar spiral antenna for passive radio frequency identification (RFID) tag application at UHF band is designed and optimized using the Artificial Bee Colony (ABC) algorithm. The optimization goals are antenna size minimization, gain maximization, conjugate matching, and in consequence the maximization of the read range. The antenna dimensions were optimized and evaluated using ABC in conjunction with commercial electromagnetic (EM) software. The comparison of the results obtained by ABC to respective ones of other popular evolutionary algorithms show that ABC can be efficiently applied to tag antenna design problems. To validate the theoretical results, designed RFID tags were fabricated, and their reading efficiency was evaluated experimentally. The results of simulation and those received via measurements prove that the proposed method for the design of passive RFID tag antennas is efficient, as antennas with dimensions less than 3 cm, gain that reaches the value of 1.6 dBi, and read range about 6 m were obtained.

Hybrid-Fractal Direct Radiating Antenna Arrays With Small Number of Elements for Satellite Communications

The fractal technique is proposed as an effective procedure for the design of direct radiating arrays (DRAs) with specific operational features, capable to serve a satellite communication network. Large fractal multibeam antenna arrays were synthesized, which meet the requirements of high end of coverage (EOC) directivity, low side lobe level and suppressed level of grating lobes. Their main advantage is the small number of elements and driving points, attributes that minimize the cost and the manufacturing complexity of the system. To obtain the high performance properties of the DRAs, the fractal algorithm was used as a fundamental process and then modification of the original arrays was made by deterministic concepts, and by combining fractal arrays with different generators. So, the entire complex process, produced arrays that would be termed as ¿hybrid - fractal¿ antenna arrays.

Methods to Design Microstrip Antennas for Modern Applications

The evolution of modern wireless communications systems has increased dramatically the demand for antennas, capable to be embedded in portable, or not, devices which serve a wireless land mobile or terrestrial-satellite network. With time and requirements, these devices become smaller in size and hence the antennas required for transmit and receive signals have also to be smaller and lightweight. As a matter of fact, microstrip antennas can meet these requirements. As they are lightweight and have low profile it is feasible them to be structured conformally to the mounting hosts. Moreover, they are easy fabricated, have low cost and are easy integrated into arrays or into microwave printed circuits. So, they are attractive choices for the above mentioned type of applications. For all that, the design of a microstrip antenna is not always an easy problem and the antenna designer is faced with difficulties coming from a) the inherent disadvantages of a printed resonant antenna element, for example the narrow impedance bandwidth, and b) the various requirements of the specific applications, which concern the operation of the radiating element, and can not be satisfied by a printed scheme with an ordinary configuration. For example, it would be demanded, the microstrip element to have gain characteristics that potentially incommensurate to its size or/and frequency bandwidth greater than the element could give, taking into account that it operates as a resonant cavity. Moreover, the rapid development in the field of Land Mobile Telephony as well as in the field of Wireless Local Area Networks(WLANs) demands devices capable to operate in more than one frequency bands. So the design of a printed antenna with intend to conform to multiple communications protocols, for example the IEEE 802.11b/g, in the band of 2.4GHz, and the IEEE 802.11a at 5.3GHz and 5.8GHz, would be a difficult task but at the same time a challenge for the designer. Counting in the above the possibility the device, and so the antenna, to serve terrestrial and also satellite navigation systems the problem of the antenna design is even more complicated. In this chapter techniques will be analysed, to design microstrip antennas that combine the attributes mentioned above which make them suitable for modern communications applications. Specific examples will be also presented for every case.