883 resultados para Reconfigurable microstrip antennas
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This work presents a theoretical and numerical analysis of structures using frequency selective surfaces applied on patch antennas. The FDTD method is used to determine the time domain reflected fields. Applications of frequency selective surfaces and patch antennas cover a wide area of telecommunications, especially mobile communications, filters and WB antennas. scattering parameters are obteained from Fourier Transformer of transmited and reflected fields in time domain. The PML are used as absorbing boundary condition, allowing the determination of the fields with a small interference of reflections from discretized limit space. Rectangular patches are considered on dielectric layer and fed by microstrip line. Frequency selective surfaces with periodic and quasi-periodic structures are analyzed on both sides of antenna. A literature review of the use of frequency selective surfaces in patch antennas are also performed. Numerical results are also compared with measured results for return loss of analyzed structures. It is also presented suggestions of continuity to this work
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This work treats of an implementation OFDMA baseband processor in hardware for LTE Downlink. The LTE or Long Term Evolution consist the last stage of development of the technology called 3G (Mobile System Third Generation) which offers an increasing in data rate and more efficiency and flexibility in transmission with application of advanced antennas and multiple carriers techniques. This technology applies in your physical layer the OFDMA technical (Orthogonal Frequency Division Multiple Access) for generation of signals and mapping of physical resources in downlink and has as base theoretical to OFDM multiple carriers technique (Orthogonal Frequency Division Multiplexing). With recent completion of LTE specifications, different hardware solutions have been developed, mainly, to the level symbol processing where the implementation of OFDMA processor in base band is commonly considered, because it is also considered a basic architecture of others important applications. For implementation of processor, the reconfigurable hardware offered by devices as FPGA are considered which shares not only to meet the high requirements of flexibility and adaptability of LTE as well as offers possibility of an implementation quick and efficient. The implementation of processor in reconfigurable hardware meets the specifications of LTE physical layer as well as have the flexibility necessary for to meet others standards and application which use OFDMA processor as basic architecture for your systems. The results obtained through of simulation and verification functional system approval the functionality and flexibility of processor implemented
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This work presents the analysis of an antenna of fractal microstrip of Koch with dielectric multilayers and inclinations in the ground plane, whose values of the angles are zero degree (without inclinations), three, seven and twelve degrees. This antenna consists of three dielectric layers arranged vertically on each other, using feeding microstrip line in patch 1, of the first layer, which will feed the remaining patches of the upper layers by electromagnetic coupling. The objective of this work is to analyze the effects caused by increase of the angle of inclination of the ground plane in some antenna parameters such as return loss, resonant frequency, bandwidth and radiation pattern. The presented results demonstrate that with the increase of the inclination angle it is possible to get antennas with characteristics multiband, with bigger bandwidth, and improving the impedance matching for each case analyzed, especially the larger angle
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This work presents techniques used to design and manufacture microstrip patch antennas for applications in portable and mobile devices. To do so, are evaluated several factors that can influence the performance of microstrip patch antennas. Miniaturization techniques are studied and employed in order to apply this type of antenna in mobile and / or mobile. The theories of microstrip patch antennas are addressed by analyzing characteristics such as constitution, kinds of patches, substrates, feeding methods, analysis methods, the main advantages and disadvantages and others. Techniques for obtaining broadband microstrip patch antennas were surveyed in literature and exemplified mainly by means of simulations and measurements. For simulations of the antennas was used the commercial software . In addition, antenna miniaturization techniques have been studied as a main concern the fundamental limits of antennas with special attention to electrically small antennas because they are directly linked to the microstrip patch antennas. Five design antennas are proposed to demonstrate the effectiveness of techniques used to obtain the microstrip patch antennas broadband and miniaturized for use in mobile devices and/or portable. For this, the proposed antennas were simulated, built and measured. The antennas are proposed to be used in modern systems of wireless communications such as DTV, GPS, IEEE 802.16, IEEE 802.11, etc. The simulations of the antennas were made in business and computer programs. The measured results were obtained with a parser Vector of networks of the Rhode and Schwarz model ZVB 14
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This paper presents an evaluative study about the effects of using a machine learning technique on the main features of a self-organizing and multiobjective genetic algorithm (GA). A typical GA can be seen as a search technique which is usually applied in problems involving no polynomial complexity. Originally, these algorithms were designed to create methods that seek acceptable solutions to problems where the global optimum is inaccessible or difficult to obtain. At first, the GAs considered only one evaluation function and a single objective optimization. Today, however, implementations that consider several optimization objectives simultaneously (multiobjective algorithms) are common, besides allowing the change of many components of the algorithm dynamically (self-organizing algorithms). At the same time, they are also common combinations of GAs with machine learning techniques to improve some of its characteristics of performance and use. In this work, a GA with a machine learning technique was analyzed and applied in a antenna design. We used a variant of bicubic interpolation technique, called 2D Spline, as machine learning technique to estimate the behavior of a dynamic fitness function, based on the knowledge obtained from a set of laboratory experiments. This fitness function is also called evaluation function and, it is responsible for determining the fitness degree of a candidate solution (individual), in relation to others in the same population. The algorithm can be applied in many areas, including in the field of telecommunications, as projects of antennas and frequency selective surfaces. In this particular work, the presented algorithm was developed to optimize the design of a microstrip antenna, usually used in wireless communication systems for application in Ultra-Wideband (UWB). The algorithm allowed the optimization of two variables of geometry antenna - the length (Ls) and width (Ws) a slit in the ground plane with respect to three objectives: radiated signal bandwidth, return loss and central frequency deviation. These two dimensions (Ws and Ls) are used as variables in three different interpolation functions, one Spline for each optimization objective, to compose a multiobjective and aggregate fitness function. The final result proposed by the algorithm was compared with the simulation program result and the measured result of a physical prototype of the antenna built in the laboratory. In the present study, the algorithm was analyzed with respect to their success degree in relation to four important characteristics of a self-organizing multiobjective GA: performance, flexibility, scalability and accuracy. At the end of the study, it was observed a time increase in algorithm execution in comparison to a common GA, due to the time required for the machine learning process. On the plus side, we notice a sensitive gain with respect to flexibility and accuracy of results, and a prosperous path that indicates directions to the algorithm to allow the optimization problems with "η" variables
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This paper deals with the design of a network-on-chip reconfigurable pseudorandom number generation unit that can map and execute meta-heuristic algorithms in hardware. The unit can be configured to implement one of the following five linear generator algorithms: a multiplicative congruential, a mixed congruential, a standard multiple recursive, a mixed multiple recursive, and a multiply-with-carry. The generation unit can be used both as a pseudorandom and a message passing-based server, which is able to produce pseudorandom numbers on demand, sending them to the network-on-chip blocks that originate the service request. The generator architecture has been mapped to a field programmable gate array, and showed that millions of numbers in 32-, 64-, 96-, or 128-bit formats can be produced in tens of milliseconds. (C) 2011 Elsevier B.V. All rights reserved.
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With the fast innovation of the hardware and software technologies using rapid prototyping devices, with application in the robotics and automation, more and more it becomes necessary the development of applications based on methodologies that facilitate future modifications, updates and enhancements in the original projected system. This paper presents a conception of mobile robots using rapid prototyping, distributing the several control actions in growing levels of complexity and using resources of reconfigurable computing proposal oriented to embed systems implementation. Software and the hardware are structuralized in independents blocks, with connection through common bus. The study and applications of new structures control that permits good performance in relation to the parameter variations. This kind of controller can be tested on different platform representing the wheeled mobile robots using reprogrammable logic components (FPGA). © 2006 IEEE.
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This paper presents a model for the control of the radiation pattern of a circular array of antennas, shaping it to address the radiation beam in the direction of the user, in order to reduce the transmitted power and to attenuate interference. The control of the array is based on Artificial Neural Networks (ANN) of the type RBF (Radial Basis Functions), trained from samples generated by the Wiener equation. The obtained results suggest that the objective was reached.
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Nos últimos anos, com o surgimento de novos serviços e equipamentos para o sistema de comunicação móvel com maiores larguras de banda de operação e ocupando espaços cada vez menores, o desenvolvimento de novas antenas de bandas largas e com dimensões pequenas se tornou um dos principais desafios das pesquisas na área de antenas. Neste trabalho, duas estruturas de antenas de bandas largas e dimensões reduzidas foram analisadas e otimizadas. Na primeira parte, a antena filamentar monopolo dobrado (Wire Built-in Folded Monopole Antenna, W-BFMA) foi investigada e teve sua largura de banda otimizada, conectada a linha de alimentação em diferentes impedâncias. Para modelar a estrutura da antena W-BFMA foi usado o método numérico dos momentos (Method of Moments - MoM), e para sua otimização os métodos: paramétrico, hill climbing e algoritmo genético (AG). Programas computacionais baseados na linguagem Matlab foram desenvolvidos para modelagem, otimização e cálculos das principais curvas características da antena W-BFMA. Na segunda parte, duas diferentes configurações de antenas monopolos planos usando a tecnologia de banda ultra-larga (Ultra- Wideband Antenna, UWB) foram investigadas e otimizadas com a ajuda do programa comercial Computer Simulation Technology (CST) Microwave Studio. Ambas as antenas UWB foram alimentadas por uma linha de microfita (microstrip line) na impedância de 50Ω. A antena UWB que apresentou melhor resultado teve o seu protótipo construído, as principais curvas características, tais como: perda de retorno, ganho, distribuição de corrente e diagrama de radiação foram analisadas. Os resultados simulados foram comparados com resultados obtidos experimentalmente.
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The emergence of wavelength-division multiplexing (WDM) technology provides the capability for increasing the bandwidth of synchronous optical network (SONET) rings by grooming low-speed traffic streams onto different high-speed wavelength channels. Since the cost of SONET add–drop multiplexers (SADM) at each node dominates the total cost of these networks, how to assign the wavelength, groom the traffic, and bypass the traffic through the intermediate nodes has received a lot of attention from researchers recently. Moreover, the traffic pattern of the optical network changes from time to time. How to develop dynamic reconfiguration algorithms for traffic grooming is an important issue. In this paper, two cases (best fit and full fit) for handling reconfigurable SONET over WDM networks are proposed. For each approach, an integer linear programming model and heuristic algorithms (TS-1 and TS-2, based on the tabu search method) are given. The results demonstrate that the TS-1 algorithm can yield better solutions but has a greater running time than the greedy algorithm for the best fit case. For the full fit case, the tabu search heuristic yields competitive results compared with an earlier simulated annealing based method and it is more stable for the dynamic case.
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We propose an efficient scheduling scheme that optimizes advance-reserved lightpath services in reconfigurable WDM networks. A re-optimization approach is devised to reallocate network resources for dynamic service demands while keeping determined schedule unchanged.
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The emergence of Wavelength Division Multiplexing (WDM) technology provides the capability for increasing the bandwidth of Synchronous Optical Network (SONET) rings by grooming low-speed traffic streams onto different high-speed wavelength channels. Since the cost of SONET add-drop multiplexers (SADM) at each node dominates the total cost of these networks, how to assign the wavelength, groom in the traffic and bypass the traffic through the intermediate nodes has received a lot of attention from researchers recently.
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In this work, we present a numerical study of the use of reconfigurable arrays (RCA) for vibro-acoustography (VA) beam formation. A parametric study of the aperture selection, number of channels, number of elements, focal distance, and steering parameters is presented to show the feasibility and evaluate the performance of VA imaging based on RCA. The transducer aperture was based on two concentric arrays driven by two continuous-wave or toneburst signals at slightly different frequencies. The mathematical model considers a homogeneous, isotropic, inviscid medium. The point-spread function of the system is calculated based on angular spectrum methods using the Fresnel approximation for rectangular sources. Simulations considering arrays with 50 x 50 to 200 x 200 elements with number of channels varying in the range of 32 to 128 are evaluated to identify the best configuration for VA. Advantages of two-dimensional and RCA arrays and aspects related to clinical importance of the RCA implementation in VA, such as spatial resolution, image frame rate, and commercial machine implementation, are discussed. It is concluded that RCA transducers can produce spatial resolution similar to confocal transducers and steering is possible in the elevational and azimuthal planes. Optimal settings for number of elements, number of channels, maximum steering, and focal distance are suggested for VA clinical applications. Furthermore, an optimization for beam steering based on the channel assignment is proposed for balancing the contribution of the two waves in the steered focus.
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The Pierre Auger Observatory is exploring the potential of the radio detection technique to study extensive air showers induced by ultra-high energy cosmic rays. The Auger Engineering Radio Array (AERA) addresses both technological and scientific aspects of the radio technique. A first phase of AERA has been operating since September 2010 with detector stations observing radio signals at frequencies between 30 and 80 MHz. In this paper we present comparative studies to identify and optimize the antenna design for the final configuration of AERA consisting of 160 individual radio detector stations. The transient nature of the air shower signal requires a detailed description of the antenna sensor. As the ultra-wideband reception of pulses is not widely discussed in antenna literature, we review the relevant antenna characteristics and enhance theoretical considerations towards the impulse response of antennas including polarization effects and multiple signal reflections. On the basis of the vector effective length we study the transient response characteristics of three candidate antennas in the time domain. Observing the variation of the continuous galactic background intensity we rank the antennas with respect to the noise level added to the galactic signal.
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This paper aims to provide an improved NSGA-II (Non-Dominated Sorting Genetic Algorithm-version II) which incorporates a parameter-free self-tuning approach by reinforcement learning technique, called Non-Dominated Sorting Genetic Algorithm Based on Reinforcement Learning (NSGA-RL). The proposed method is particularly compared with the classical NSGA-II when applied to a satellite coverage problem. Furthermore, not only the optimization results are compared with results obtained by other multiobjective optimization methods, but also guarantee the advantage of no time-spending and complex parameter tuning.