Nanbo Jin

Advances in Particle Swarm Optimization for Antenna Designs: Real-Number, Binary, Single-Objective and Multiobjective Implementations

The particle swarm optimization (PSO) is a recently developed evolutionary algorithm (EA) based on the swarm behavior in the nature. This paper presents recent advances in applying a versatile PSO engine to real-number, binary, single-objective and multiobjective optimizations for antenna designs, with a randomized Newtonian mechanics model developed to describe the swarm behavior. The design of aperiodic (nonuniform and thinned) antenna arrays is presented as an example for the application of the PSO engine. In particular, in order to achieve an improved peak sidelobe level (SLL), element positions in a nonuniform array are optimized by real-number PSO (RPSO). On the other hand, in a thinned array, the on/off state of each element is determined by binary PSO (BPSO). Optimizations for both nonuniform arrays and thinned arrays are also expanded to multiobjective cases. As a result, nondominated designs on the Pareto front enable one to achieve other design factors than the peak SLL. Optimized antenna arrays are compared with periodic arrays and previously presented aperiodic arrays. Selected designs fabricated and measured to validate the effectiveness of PSO in practical electromagnetic problems

Parallel particle swarm optimization and finite- difference time-domain (PSO/FDTD) algorithm for multiband and wide-band patch antenna designs

This paper presents a novel evolutionary optimization methodology for multiband and wide-band patch antenna designs. The particle swarm optimization (PSO) and the finite-difference time-domain (FDTD) are combined to achieve the optimum antenna satisfying a certain design criterion. The antenna geometric parameters are extracted to be optimized by PSO, and a fitness function is evaluated by FDTD simulations to represent the performance of each candidate design. The optimization process is implemented on parallel clusters to reduce the computational time introduced by full-wave analysis. Two examples are investigated in the paper: first, the design of rectangular patch antennas is presented as a test of the parallel PSO/FDTD algorithm. The optimizer is then applied to design E-shaped patch antennas. It is observed that by using different fitness functions, both dual-frequency and wide-band antennas with desired performance are obtained by the optimization. The optimized E-shaped patch antennas are analyzed, fabricated, and measured to validate the robustness of the algorithm. The measured less than - 18 dB return loss (for dual-frequency antenna) and 30.5% bandwidth (for wide-band antenna) exhibit the prospect of the parallel PSO/FDTD algorithm in practical patch antenna designs.

A novel patch antenna with switchable slot (PASS): dual-frequency operation with reversed circular polarizations

In this paper, the recently proposed patch antenna with switchable slot (PASS) concept is implemented to design a novel reconfigurable antenna with both frequency and polarization diversities. Using only one switch and a single patch, the antenna operates at 4.20 GHz with right-handed circular polarization and at 4.55 GHz with left-handed circular polarization. The fabricated antenna has both an acceptable return loss and a broadside axial ratio (AR) lower than 2 dB at each operation frequency. The frequency and polarization diversities of this design could potentially improve the reliability of wireless communication systems

Hybrid Real-Binary Particle Swarm Optimization (HPSO) in Engineering Electromagnetics

The applications of a hybrid real-binary particle swarm optimization (HPSO) algorithm in engineering electromagnetics are described. In HPSO, each candidate design is designated by a hybridized vector consisting of both real and binary variables. These variables are evolved in the optimization by following the velocity/position updating formulas of real-number PSO (RPSO) and binary PSO (BPSO), respectively. Both single- and multi-objective implementations of the algorithm are validated by functional testbeds. Simulation and measurement results of three examples, i.e, the design of a non-uniform antenna array, a multilayered planar radar absorbing material (RAM) and a dual-band handset antenna are presented, in order to illustrate the effectiveness of the algorithm in representative topology exploration and material selection problems.

Analysis and Particle Swarm Optimization of Correlator Antenna Arrays for Radio Astronomy Applications

A novel design methodology is presented for correlator antenna arrays in radio astronomy applications. In order to characterize the spatial-filter-like performance of a correlator array, an analyzer is developed to calculate its - coverage and synthesized beam, along with the capability to simulate the Earth rotation effect and the image retrieval process. On the other hand, particle swarm optimization (PSO) is applied to determine the locations of antenna elements in typical open-ended and closed array configurations (such as the ldquoYrdquo and the Reuleaux triangle), in order to achieve either the maximum - coverage or a synthesized beam with the lowest sidelobe level (SLL). Optimized arrays are observed to outperform uniform arrays and representative existing designs.

Particle swarm optimization for antenna designs in engineering electromagnetics

This paper presents recent advances in applying particle swarm optimization (PSO) to antenna designs in engineering electromagnetics. By linking the PSO kernel with external electromagnetic (EM) analyzers, the algorithm has the flexibility to handle both real and binary variables, as well as multiobjective problems with more than one optimization goal. Three examples, including the designs of a dual-band patch antenna, an artificial ground plane of a surface wave antenna, and an aperiodic antenna array, are presented. Both simulation and measurement results are provided to illustrate the effectiveness of applying the swarm intelligence to design antennas with desired frequency response and radiation characteristics for practical EM applications.

A novel reconfigurable patch antenna with both frequency and polarization diversities for wireless communications

A novel reconfigurable patch antenna that applies the PASS concept is presented in this paper to obtain both frequency and polarization diversities for wireless communications. With single patch and single feed, the antenna operates at two different frequencies with a frequency ratio of 1.055, similar radiation pattern and opposite circular polarizations. Experiments are carried out to demonstrate the feasibility of the design, and satisfactory axial ratios of 1.86 dB and 1.99 dB are obtained. The presented methodology is very promising in antenna design for satellite and mobile communications, which require multi-frequency operation to enhance the channel capacity, and different polarizations to prevent crosstalk between the channels.

Particle swarm optimization of miniaturized quadrature reflection phase structure for low-profile antenna applications

A new terminology, quadrature reflection phase structure (QRPS), is defined. Without applying traditional methods, such as effective circuit modeling, a parallel PSO/FDTD (particle swarm optimization/finite difference time-domain) algorithm is utilized to determine a QRPS topology based on its reflection phase characteristics. The optimized QRPS has miniaturized dimensions and provides good performance in a surface wave antenna application. The parallel PSO/FDTD algorithm has the potential to be promising in more complicated QRPS/EBG designs, by exploiting the robustness of the PSO kernel, the accuracy of a full-wave simulator and faster computation due to its parallel implementation.

Real-Number and Binary Multi-Objective Particle Swarm Optimizations: Aperiodic Antenna Array Designs

A classic engineering problem, the design of aperiodic antenna arrays, is revisited in this paper by applying real-number and binary MOPSO algorithms. The peak SLL and other design criteria such as the beamwidth and the element number are traded off to find the best design strategy. The effectiveness of the algorithms is validated by comparing the optimization results with conventional periodic arrays and existing methodologies such as the statistical density tapering

Particle swarm optimization for multi-band handset antenna designs: A hybrid real-binary implementation

The hybrid real-binary particle swarm optimization (HPSO) algorithm is applied in this paper to design a dual-band handset patch antenna operating at 1.8 GHz and 2.4 GHz. The unique hybrid representation of candidate antenna designs using real and binary variables enables the optimizer to benefit from the advantages of both continuous and discrete optimization techniques. With the fitness function evaluated by a MoM-based full-wave simulator, the design is accomplished in a quite limited space with a dimension of 0.23 lambdagtimes0.13 lambdag at 1.8 GHz. Measurement results demonstrate that the optimal antenna has satisfactory impedance matching and radiation characteristics at desired operating frequencies.