Recent Advances in Antenna Design for 5G Heterogeneous Networks

The aim of this book is to highlight up to date exploited technologies and approaches in terms of antenna designs and requirements. In this regard, this book targets a broad range of subjects, including the microstrip antenna and the dipole and printed monopole antenna. The varieties of antenna designs, along with several different approaches to improve their overall performance, have given this book a great value, in which makes this book is deemed as a good reference for practicing engineers and under/postgraduate students working in this field. The key technology trends in antenna design as part of the mobile communication evolution have mainly focused on multiband, wideband, and MIMO antennas, and all have been clearly presented, studied and implemented within this book. The forthcoming 5G systems consider a truly mobile multimedia platform that constitutes a converged networking arena that not only includes legacy heterogeneous mobile networks but advanced radio interfaces and the possibility to operate at mm wave frequencies to capitalize on the large swathes of available bandwidth. This provides the impetus for a new breed of antenna design that, in principle, should be multimode in nature, energy efficient, and, above all, able to operate at the mm wave band, placing new design drivers on the antenna design. Thus, this book proposes to investigate advanced 5G antennas for heterogeneous applications that can operate in the range of 5G spectrums and to meet the essential requirements of 5G systems such as low latency, large bandwidth, and high gains and efficiencies

Multi-Objective Design Optimization of Planar Yagi-Uda Antenna Using Physics-Based Surrogates and Rotational Design Space Reduction

AbstractA procedure for low-cost multi-objective design optimization of antenna structures is discussed. The major stages of the optimization process include: (i) an initial reduction of the search space aimed at identifying its relevant subset containing the Pareto-optimal design space, (ii) construction—using sampled coarse-discretization electromagnetic (EM) simulation data—of the response surface approximation surrogate, (iii) surrogate optimization using a multi-objective evolutionary algorithm, and (iv) the Pareto front refinement. Our optimization procedure is demonstrated through the design of a planar quasi Yagi-Uda antenna. The final set of designs representing the best available trade-offs between conflicting objectives is obtained at a computational cost corresponding to about 172 evaluations of the high-fidelity EM antenna model