Multiobjective Differential Evolution for Higher-Dimensional Multimodal Multiobjective Optimization

In multimodal multiobjective optimization problems(MMOPs),there are several Pareto optimal solutions corre-sponding to the identical objective vector.This paper proposes a new differential evolution algorithm to solve MMOPs with higher-dimensional decision variables.Due to the increase in the dimensions of decision variables in real-world MMOPs,it is diffi-cult for current multimodal multiobjective optimization evolu-tionary algorithms(MMOEAs)to find multiple Pareto optimal solutions.The proposed algorithm adopts a dual-population framework and an improved environmental selection method.It utilizes a convergence archive to help the first population improve the quality of solutions.The improved environmental selection method enables the other population to search the remaining decision space and reserve more Pareto optimal solutions through the information of the first population.The combination of these two strategies helps to effectively balance and enhance conver-gence and diversity performance.In addition,to study the per-formance of the proposed algorithm,a novel set of multimodal multiobjective optimization test functions with extensible decision variables is designed.The proposed MMOEA is certified to be effective through comparison with six state-of-the-art MMOEAs on the test functions.

Over-the-Air Performance Evaluation in Indoor and Outdoor Multipath Propagation Channels of Antenna Diversity Systems inside Anechoic Chamber

With the ever-growing requirement for higher data rates, terminals supporting multiple-input multiple-output (MIMO) technologies are being developed for next-generation. As for wireless device manufacturers, a radio performance evaluation of multi-antenna terminals in desired environments is mandatory before product release. This paper discusses the Over the Air (OTA) performance evaluation of antenna diversity systems in Indoor and Outdoor multi-path propagation channel models inside anechoic chamber, in terms of correlation coefficients and diversity gain (DG). These channel models have been emulated in terms of angles of arrivals (AoA) and cross-polarization ratio (XPR) with Rayleigh fading. For this purpose, SATIMO SG24 measurement system has been used. However, the actual configuration of this system is not able to emulate desired realistic environments. Therefore, an innovative methodology based on the SG24 probes control has been developed. The obtained results in simulations and measurements have shown a good agreement.

Emulation of Realistic Multi-Path Propagation Channels inside an Anechoic Chamber for Antenna Diversity Measurements

As antennas are inherently included recommended in Over-The-Air (OTA) testing, it is important to also consider realistic channel models for the multiple-input multiple-output (MIMO) device performance evaluation. This paper aims to emulate realistic multi-Path propagation channels in terms of angles of arrivals (AoA) and cross-polarization ratio (XPR) with Rayleigh fading, inside an anechoic chamber, for antenna diversity measurements. In this purpose, a practical multi-probe anechoic chamber measurement system (MPAC) with 24 probe antennas (SATIMO SG24) has been used. However, the actual configuration of this system is not able to reproduce realistic channels. Therefore, a new method based on the control of the SG24 probes has been developed. At first time, this method has been validated numerically through the comparison of simulated and analytical AoA probability density distributions. At the second time, the performance of an antenna diversity system inside the SG24 has been performed in terms of the correlation coefficient and diversity gain (DG) using an antenna reference system. Simulated and measurements results have shown a good agreement.

Ensemble Classifier Design Based on Perturbation Binary Salp Swarm Algorithm for Classification

Multiple classifier system exhibits strong classification capacity compared with single classifiers,but they require significant computational resources.Selective ensemble system aims to attain equivalent or better classification accuracy with fewer classifiers.However,current methods fail to identify precise solutions for constructing an ensemble classifier.In this study,we propose an ensemble classifier design technique based on the perturbation binary salp swarm algorithm(ECDPB).Considering that extreme learning machines(ELMs)have rapid learning rates and good generalization ability,they can serve as the basic classifier for creating multiple candidates while using fewer computational resources.Meanwhile,we introduce a combined diversity measure by taking the complementarity and accuracy of ELMs into account;it is used to identify the ELMs that have good diversity and low error.In addition,we propose an ECDPB with powerful optimizing ability;it is employed to find the optimal subset of ELMs.The selected ELMs can then be used to forman ensemble classifier.Experiments on 10 benchmark datasets have been conducted,and the results demonstrate that the proposed ECDPB delivers superior classification capacity when compared with alternative methods.

Revisit to Mutual Coupling Effects on Multi-Antenna Systems

Due to space limitation,mutual coupling occurs almost invisibly in array antennas.In this paper,the mutual coupling effects on the two most popular categories of array antennas,i.e.,phased arrays and multiple-input multiple-output(MIMO)antennas,are reviewed.Some misconceptions regarding the mutual coupling effects are uncovered.It is shown that the steering pattern of a phased array at an arbitrary scan-ning angle can be readily calculated once the embedded radiation patterns of the array elements(including the mutual coupling effect)are obtained.As antenna spacing decreases,absorption loss increases,yet the phase terms tend to add up constructively as antenna spacing reduces,which may overcompensate the absorption loss due to mutual coupling.Thus,the array efficiency may be increased by reducing the antenna spacing.A patch antenna array is used to illustrate this phenomenon.It is further shown that while mutual coupling tends to reduce the correlation of two-element arrays,it has a negligible effect on the overall correlations of larger arrays.Finally,various mutual coupling reduction techniques are briefly presented.Two feasible techniques for large planar arrays are used to illustrate the benefits of array decoupling.