Preface

Modern communications systems require the use of multiple antennas to meet key performance indicators. In particular, 5G and 6G mobile communications rely on the existence of antenna arrays to achieve a wide variety of desired use cases. Several antenna designs are evolving to improve systems that incorporate Multiple-Input Multiple-Output (MIMO), massive MIMO, cell-free MIMO, and other techniques. The expected convergence of terrestrial and non-terrestrial networks also requires research on antennas and antenna arrays. In this context, this book presents recent developments in modern design and analysis of antenna array techniques. It consists of six chapters and is useful for interested readers and those working with antenna arrays, including researchers, engineers, and students.

Chapter 1 presents the design and analysis of three-dimensional GPS microstrip antennas operating at 1.57542 GHz. The simulations are compared with experimental results and show the impact of several 3D geometries on figures of merit such as the phase response. The proposed antenna presents a nearly uniform phase response when the 3D structure is bent by angles ranging from 15 degrees to 30 degrees without compromising performance. A Finite-Difference Time-Domain scheme is discussed to clarify the interplay between the proposed antennas and several ground plane configurations.

Chapter 2 discusses present and future research and development directions regarding spaceborne Synthetic Aperture Radar (SAR) antenna arrays. It includes theoretical analysis, simulation results, and experimental verification. The authors explain the drawbacks of traditional antenna arrays, which include large volumes, weights, and manufacturing costs, among others. Then some breakthroughs in antenna architectures are presented, such as the metamaterial and periodic reflector array antennas. The chapter also discusses aperiodic, parabolic, and hypersurface antennas, indicating characteristics and trends of spaceborne SAR antenna arrays.

Chapter 3 describes a method to design antenna arrays using machine learning. Within the context of array thinning, the goal is to systematically remove elements without change in the performance. The presented results include a performance evaluation of arrays with and without thinning and the radiation characteristics. The authors also discuss the characteristics of deep learning and other learning algorithms in the design of antenna arrays with thinning.

Chapter 4 investigates the reduction of the sidelobe level associated with antenna arrays using enhanced firefly and genetic algorithms. The presented results show that the enhanced firefly algorithm outperforms the genetic algorithm. The antenna array side lobe level is optimized without degrading performance with respect to the beam width. The author also discusses the advantages of reducing the number of active elements in an antenna array by turning them off.

Chapter 5 presents an analysis of coverage considering pathloss models adequate for studying digital terrestrial TV and TV white space. It analyzes different propagation models in very high and ultra-high frequency bands. Then, the authors use the best model to find the coverage of the incumbent transmitter and the free channels for secondary use.

Chapter 6 focuses on the development of multipurpose antennas having different applications in communications and detection, among other applications. It discusses techniques for antenna array reconfiguration, with special emphasis on graphene antennas. The chapter includes a few antenna array designs, which help in understanding reconfiguration for distinct applications.

> **Hussain M. Al-Rizzo** Department of Systems Engineering, DSTEM College, University of Arkansas Little Rock, USA

> > **Nijas Kunju** Ansys Inc.,

Bangalore, India

**Aldebaro Klautau**

Computer Engineering Department, Federal University of Para, Belem, Brazil
