J. Basterrechea

Comparison of Different Heuristic Optimization Methods for Near-Field Antenna Measurements

A comparison between different modern heuristic optimization methods applied to antenna far-field radiation pattern reconstruction from planar near-field data is presented in this paper. The antenna under test is represented by means of equivalent magnetic currents (EMC) whose components are optimized using several heuristic algorithms such as simulated annealing (SA), genetic algorithms (GA), and particle swarm optimization (PSO), as well as a traditional local optimization method, the Nelder Mead downhill simplex algorithm. Several schemes for GA (classical real-valued and binary encoding, and their hybrid versions) and PSO (global or local topologies with synchronous or asynchronous updates of the swarm) have been considered in the analysis and the pros and cons of each one are reported and discussed. A study of the performance and limitations of each algorithm using as a canonical problem a small size antenna aperture, along with results of near-field to far-field (NF-FF) transformation are also included

HYBRID PARTICLE SWARM-BASED ALGORITHMS AND THEIR APPLICATION TO LINEAR ARRAY SYNTHESIS

Aheuristic particle swarm optimization (PSO) based algorithm is presented in this work and the novel hybrid approach is applied to linear array synthesis considering complex weights and directive element patterns so as to analyze its usefulness and limitations. Basically, classical PSO schemes are modified by introducing a tournament selection strategy and the downhill simplex local search method, so that the hybrid algorithms proposed combine the strengths of the PSO to initially explore the search space, the pressure exerted by the genetic selection operator to manage and speed up the search, and finally, the ability of the local optimization technique to quickly descend to the optimum solution. Four classical real-valued PSO schemes are taken as reference and synthesis results for a 60-element linear array comparing those classical schemes and the hybridized ones are reported and discussed in order to show the improvements achieved by the hybrid approaches.

Synthesis of Planar Arrays Using a Modified Particle Swarm Optimization Algorithm by Introducing a Selection Operator and Elitism

A modifled particle swarm optimization (PSO) algorithm applied to planar array synthesis considering complex weights and directive element patterns is presented in this paper. The modern heuristic classical PSO scheme with asynchronous updates of the swarm and a global topology has been modifled by introducing tournament selection, one of the most efiective selection strategies performing in genetic algorithms the equivalent role to natural selection, and elitism. The modifled PSO proposed combines the abilities of the classical PSO to explore the search space and the pressure exerted by the selection operator to speed up convergence. Regarding the optimization problem, the synthesis of the feeds for rectangular planar arrays consisting of microstrip patches or subarrays of microstrip patches is considered. Results comparing the performance and limitations of classical and modifled PSO-based schemes are included considering both test functions and planar array complex synthesis to best meet certain far-fleld radiation pattern restrictions given in terms of 3D-masks. Finally, representative synthesis results for sector antennas for worldwide interoperability for microwave access (WiMAX) applications are also included and discussed.

Optimization of the Coverage Area for DVB-T Single Frequency Networks Using a Particle Swarm Based Method

Single frequency networks (SFN) are usually considered to deploy OFDM modulation based digital broadcast systems, exploiting the multipath tolerance of the OFDM receivers, which are capable of combining signals coming from several transmitters with different propagation delays. In this work, a planning tool is proposed to improve the coverage area in SFN networks, optimizing transmission parameters such as the transmitters delay or power, using 3D digital terrain maps along with a propagation prediction tool to estimate the power received at each location inside the coverage area. A heuristic particle swarm optimization algorithm is used (PSO) to optimize transmission parameters. The approach proposed makes it possible to consider several configurations regarding both transmitters and receivers. Preliminary test results are shown for a SFN with eighteen transmitters and omnidirectional radiators at both sides that demonstrate the usefulness of the approach. Furthermore, results considering receivers with directive antennas as well as transmitters with sectored antennas are also included and discussed.

Coverage optimization and power reduction in SFN using simulated annealing

An approach that predicts the propagation, models the terrestrial receivers and optimizes the performance of single frequency networks (SFN) for digital video broadcasting in terms of the final coverage achieved over any geographical region, enhancing the most populated areas, is proposed in this paper. The effective coverage improvement and thus, the self-interference reduction in the SFN is accomplished by optimizing the internal static delays, sector antenna gain, and both azimuth and elevation orientation for every transmitter within the network using the heuristic simulated annealing (SA) algorithm. Decimation and elevation filtering techniques have been considered and applied to reduce the computational cost of the SA-based approach, including results that demonstrate the improvements achieved. Further representative results for two SFN in different scenarios considering the effect on the final coverage of optimizing any of the transmitter parameters previously outlined or a combination of some of them are reported and discussed in order to show both, the performance of the method and how increasing gradually the complexity of the model for the transmitters leads to more realistic and accurate results.

Heuristic optimization of DVB-T/H SFN coverage using PSO and SA algorithms

This paper studies two of the available heuristic algorithms to optimize the digital broadcasting networks planning. Particle Swarm Optimization (PSO) and Simulated Annealing (SA) are compared working in different OFDM modes. These algorithms manipulate the information of the network with static delays in order to maximize the covered area as well as possible at minimum cost. Particle Swarm Optimization (PSO) and Simulated Annealing (SA) are compared working in a different OFDM modes and synchronization strategies. Furthermore, they have been used to estimate the coverage and the interference degree of the network planning placed in the Basque Country, in northern Spain.

Multilayer FSS Optimizer based on PSO and CG-FFT

Traditionally, Frequency Selective Surfaces (FSS) are designed to produce a certain spectral response, in one or more frequency bands, using a methodology that manually tunes and simulates the behavior of the structure. In some cases, due to the high filtering requirements of an application, it could be necessary make FSS with several periodic surfaces, in order to improve the frequency response of the final prototype. This process is difficult to be carried out if the filtering response to synthesize cannot be directly obtained with a combination of classical FSS unit cell geometries. To overcome this problem, in this paper a methodology of optimization that automates the hard and costly search is introduced, combining the PSO and an analysis methodology of structures with several periodic surfaces that act as the cost function: the Conjugate Gradient Fast Fourier Transform (CG-FFT). This approximation uses a multilayer Green function calculated applying the transmission line model that considers the mutual coupling effects by translating the field from the source FSS to the other periodic surfaces. Representative results including the optimization of a three layer FSS with two planar periodic surfaces are reported and discussed in order to show the usefulness of the approach proposed.

Coverage optimization in single frequency Networks using simulated annealing

In the last years, the migration from analog to digital terrestrial television systems has favored the deployment of Single Frequency Networks (SFN), more efficient from a spectrum point of view, to provide DVB-T services in larger geographical areas through the reuse of frequencies. However, the planning of a SFN is not a trivial task, since the designer must find a trade-off between the quality of service (QoS) required in a geographical area and the overall cost involving the deployment and maintenance of such a network, which depends primarily on the number of transmitters needed and their power. In this work, a simulated annealing (SA) based approach applied to improve the overall coverage in a SFN by optimizing transmitters parameters such as the static delay or the gain and orientation to be applied to the sector antennas, is presented. For this purpose, the approach is divided into three blocks that work as a whole: A) A propagation prediction tool, B) A receiver behavior modeling, including different methods for the FFT window positioning and echoes combination, and C) SA, used to improve the coverage over the desired area according to certain QoS requirements. Results for two SFN are included in order to demonstrate the usefulness of the method.

Analysis of single layer multiple concentric ring elements in reflectarray antennas

In this paper, multiple concentric rings are considered as phase elements in reflectarrays and the benefits of these single layer rings are compared to conventional reflective structures (multi and single layer, rectangular or elliptical printed patches) when applied to the design of reflectarrays. These ring-shaped structures have got, as the main advantages, the ease of manufacture and the wide range of phase obtained, exceeding easily 1000 degrees. The analysis of the structures is made by means of the CG-FFT method. The simulations are carried out in the Ku band, the one commonly used in Direct Broadcast Satellite applications (DBS). In order to determine the effect of the manufacturing tolerances, results of a test carried out with a simulated reflectarray are included, using a PSO based algorithm to perform the phase synthesis.

A Tool To Analyze The Response of EMC Chambers

A method for the analysis of anechoic and semianechoic chambers in the low frequency range is presented in this work. The method combines homogeneization with geometrical optics to account for multiple reflections in absorber lined chambers. Image theory is used to speed up the computation. The method is able to deal with different kind of absorbers (multilayer, pyramidal, hybrid) with their geometrical dimensions and shape stating the upper frequency limit of validity of the approach. Both dielectric and magnetic lossy materials are considered. The method has been implemented in a software tool with a GUI and allows the user an easy introduction of geometrical data for both the screening and the absorbers.