
Advanced Antenna Array Engineering for 6G and Beyond Wireless Communications
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Reviews advances in the design and deployment of antenna arrays for future generations of wireless communication systems, offering new solutions for the telecommunications industry
Advanced Antenna Array Engineering for 6G and Beyond Wireless Communications addresses the challenges in designing and deploying antennas and antenna arrays which deliver 6G and beyond performance with high energy efficiency and possess the capability of being immune to interference caused by different systems mounted on the same platforms. This timely and authoritative volume presents innovative solutions for developing integrated communications networks of high-gain, individually-scannable, multi-beam antennas that are reconfigurable and conformable to all platforms, thus enabling the evolving integrated land, air and space communications networks.
The text begins with an up-to-date discussion of the engineering issues facing future wireless communications systems, followed by a detailed discussion of different beamforming networks for multi-beam antennas. Subsequent chapters address problems of 4G/5G antenna collocation, discuss differentially-fed antenna arrays, explore conformal transmit arrays for airborne platforms, and present latest results on fixed frequency beam scanning leaky wave antennas as well as various analogue beam synthesizing strategies. Based primarily on the authors' extensive work in the field, including original research never before published, this important new volume:
* Reviews multi-beam feed networks, array decoupling and de-scattering methods
* Provides a systematic study on differentially fed antenna arrays that are resistant to interference caused by future multifunctional/multi-generation systems
* Features previously unpublished material on conformal transmit arrays based on Huygen's metasufaces and reconfigurable leaky wave antennas
* Includes novel algorithms for synthesizing and optimizing thinned massive arrays, conformal arrays, frequency invariant arrays, and other future arrays
Advanced Antenna Array Engineering for 6G and Beyond Wireless Communications is an invaluable resource for antenna engineers and researchers, as well as graduate and senior undergraduate students in the field.
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Persons
Y. Jay Guo, PhD, is the Director of the Global Big Data Technologies Centre and a Distinguished Professor at the University of Technology Sydney, Australia. He has over thirty years of academic, industrial and CSIRO experience. He holds 26 international patents, and is a Fellow of the Institute of Electrical and Electronics Engineers (IEEE), the Australian Academy of Technology and Engineering (ATSE), and the Institute of Engineering and Technology (IET). He is the author of Ground-Based Wireless Positioning and more than 550 research papers.
Richard W. Ziolkowski, PhD, is a Distinguished Professor in the Global Big Data Technologies Centre at the University of Technology Sydney, Australia, and a Professor Emeritus at the University of Arizona, USA. He is a Life Fellow of the IEEE and a Fellow of the Optical Society of America and the American Physical Society. He was the recipient of the 2019 IEEE Electromagnetics Award and was the 2005 President of the IEEE Antennas and Propagation Society. He was the 2014-2015 US Fulbright Distinguished Chair in Advanced Science and Technology sponsored by the Australian Defence Science and Technology Organization (DSTO). He is the co-editor of Metamaterials: Physics and Engineering Explorations.
Content
Author Biographies ix
Acknowledgments xi
1 A Perspective of Antennas for 5G and 6G 1
1.1 5G Requirements of Antenna Arrays 1
1.1.1 Array Characteristics 1
1.1.2 Frequency Bands 3
1.1.3 Component Integration and Antennas-in-Package (AiP) 3
1.2 6G and Its Antenna Requirements 5
1.3 From Digital to Hybrid Multiple Beamforming 6
1.3.1 Digital Beamforming 7
1.3.2 Hybrid Beamforming 8
1.4 Analog Multiple Beamforming 11
1.4.1 Butler Matrix 12
1.4.2 Luneburg Lenses 13
1.5 Millimeter-Wave Antennas 14
1.6 THz Antennas 15
1.7 Lens Antennas 16
1.8 SIMO and MIMO Multi-Beam Antennas 18
1.9 In-Band Full Duplex Antennas 19
1.10 Conclusions 20
References 20
2 Millimeter-Wave Beamforming Networks 23
2.1 Circuit-Type BFNs: SIW-Based Butler and Nolen Matrixes 23
2.1.1 Butler Matrix for One-Dimensional Multi-Beam Arrays 23
2.1.2 Butler Matrix for a 1-D Multi-Beam Array with Low Sidelobes 27
2.1.3 Butler Matrix for 2-D Multi-Beam Arrays 29
2.1.4 Nolen Matrix 34
2.2 Quasi Optical BFNs: Rotman Lens and Reflectors 36
2.2.1 Rotman Lens 36
2.2.2 Reflectors 40
2.2.2.1 Single Reflectors 41
2.2.2.2 Dual Reflectors 44
2.3 Conclusions 45
References 46
3 Decoupling Methods for Antenna Arrays 49
3.1 Electromagnetic Bandgap Structures 49
3.2 Defected Ground Structures 51
3.3 Neutralization Lines 54
3.4 Array-Antenna Decoupling Surfaces 58
3.5 Metamaterial Structures 62
3.6 Parasitic Resonators 70
3.7 Polarization Decoupling 81
3.8 Conclusions 83
References 84
4 De-scattering Methods for Coexistent Antenna Arrays 89
4.1 De-scattering vs. Decoupling in Coexistent Antenna Arrays 89
4.2 Mantle Cloak De-scattering 92
4.3 Lumped-Choke De-scattering 95
4.4 Distributed-Choke De-scattering 113
4.5 Mitigating the Effect of HB Antennas on LB Antennas 130
4.6 Conclusions 132
References 132
5 Differential-Fed Antenna Arrays 135
5.1 Differential Systems 135
5.2 Differential-Fed Antenna Elements 137
5.2.1 Linearly Polarized Differential Antennas 138
5.2.2 Circularly Polarized Differential Antennas 143
5.3 Differential-Fed Antenna Arrays 146
5.3.1 Balanced Power Dividers 147
5.3.2 Differential-Fed Antenna Arrays Employing Balanced Power Dividers 151
5.4 Differential-Fed Multi-Beam Antennas 161
5.5 Conclusions 165
References 166
6 Conformal Transmitarrays 169
6.1 Conformal Transmitarray Challenges 169
6.1.1 Ultrathin Element with High Transmission Efficiency 169
6.1.2 Beam Scanning and Multi-Beam Operation 171
6.2 Conformal Transmitarrays Employing Triple-Layer Elements 171
6.2.1 Element Designs 171
6.2.2 Conformal Transmitarray Design 173
6.3 Beam Scanning Conformal Transmitarrays 179
6.3.1 Scanning Mechanism 180
6.3.2 Experimental Results 182
6.3.3 Limits of the Beam Scanning Range 183
6.4 Conformal Transmitarray Employing Ultrathin Dual-Layer Huygens Elements 185
6.4.1 Huygens Surface Theory 186
6.4.2 Ultrathin Dual-Layer Huygens Elements 189
6.4.3 Conformal Transmitarray Design 194
6.5 Elliptically Conformal Multi-Beam Transmitarray with Wide-Angle Scanning Ability 198
6.5.1 Multi-Beam Transmitarray Design 200
6.5.2 Concept Verification Through Simulation 204
6.6 Conclusions 209
References 209
7 Frequency-Independent Beam Scanning Leaky-Wave Antennas 213
7.1 Reconfigurable Fabry-Pérot (FP) LWA 213
7.1.1 Analysis of 1-D Fabry-Pérot LWA 214
7.1.2 Effect of Cj on the Leaky-Mode Dispersion Curves 216
7.1.3 Optimization of the FP Cavity Height 218
7.1.4 Antenna Prototype and Measured Results 219
7.2 Period-Reconfigurable SIW-Based LWA 222
7.2.1 Antenna Configuration and Element Design 223
7.2.2 Suppression of Higher-Order Harmonics 226
7.2.3 Element Activation States and Scanning Properties 230
7.2.4 Results and Discussion 233
7.2.4.1 Element Pattern and Antenna Prototype 233
7.2.4.2 Radiation Patterns and S-Parameters 236
7.3 Reconfigurable Composite Right/Left-Handed LWA 240
7.3.1 Parametric Analysis 242
7.3.2 Initial Frequency-Scanning CRLH LWA 245
7.3.3 Reconfigurable Fixed-Frequency Scanning CRLH LWA 247
7.3.3.1 Antenna Configuration 247
7.3.3.2 DC Biasing Strategy 249
7.3.3.3 Simulation Results 250
7.3.3.4 Measured Results 252
7.3.3.5 Discussions 254
7.4 Two-Dimensional Multi-Beam LWA 256
7.4.1 Antenna Design 257
7.4.1.1 Horn BFN 257
7.4.1.2 Phase-Compensation Method 258
7.4.1.3 Phase Shifter Based on Phase Inverter 259
7.4.1.4 Fixed-Frequency Beam Scanning Leaky-Wave Antenna 260
7.4.2 Performance and Discussion 264
7.5 Conclusions 267
References 270
8 Beam Pattern Synthesis of Analog Arrays 275
8.1 Thinned Antenna Arrays 275
8.1.1 Modified Iterative FFT 276
8.1.2 Examples of Thinned Arrays 279
8.2 Arrays with Rotated Elements 283
8.2.1 The Pattern of an Element-Rotated Array 283
8.2.2 Vectorial Shaped Pattern Synthesis Using Joint Rotation/Phase Optimization 285
8.2.3 The Algorithm 287
8.2.4 Examples of Pattern Synthesis Based on Element Rotation and Phase 288
8.2.4.1 Flat-Top Pattern Synthesis with a Rotated U-Slot Loaded Microstrip Antenna Array 288
8.2.4.2 Circular Flat-Top Pattern Synthesis for a Planar Array with Rotated Cavity-Backed Patch Antennas 290
8.3 Arrays with Tracking Abilities Employing Sum and Difference Patterns 294
8.3.1 Nonuniformly Spaced Dipole-Rotated Linear Array 295
8.3.2 PSO-Based Element Rotation and Position Optimization 297
8.3.3 Examples 298
8.3.3.1 Synthesis of a 56-Element Sparse Linear Dipole Array 298
8.3.3.2 Synthesizing Sum and Difference Patterns with Multi-Region SLL and XPL Constraints 300
8.4 Synthesis of SIMO Arrays 301
8.4.1 Analog Dual-Beam Antenna Arrays with Linear Phase Distribution 302
8.4.2 Phase-Only Optimization of Multi-Beam Arrays 303
8.4.3 The Algorithm 306
8.4.4 Simulation Examples 306
8.5 Conclusions 308
References 308
Index 311
1
A Perspective of Antennas for 5G and 6G
The roll-out of the fifth generation (5G) of wireless and mobile communications systems has commenced, and the technology race on the sixth-generation (6G) mobile and wireless communications systems has started in earnest [1, 2]. 5G promises significantly increased capacity, massive connections, low latency, and compelling new applications. For example, device-to-device (D2D) and vehicle-to-vehicle (V2V) communication systems will help facilitate the realization of autonomous transport. The rapid access to and exchange of "Big Data" will increasingly impact real-time economic and political decisions. Similarly, highly integrated, accessible "infotainment" systems will continue to alter our social relationships and communities. Wireless power transfer will replace cumbersome, weighty, short-life batteries enabling widespread health, agriculture, and building monitoring sensor networks with much less waste impact on the environment. 6G networks aim to achieve a number of new features such as full global coverage, much greater data rates and mobility, and higher energy and cost efficiency. These will usher in new services based on virtual reality/augmented reality and artificial intelligence [3].
At the core of wireless devices, systems, networks, and ecosystems are their antennas and antenna arrays. Antennas enable the transmission and reception of electromagnetic energy. Antenna arrays enhance our abilities to direct and localize the desired energy and information transfer. To achieve the many stunning and amazing 5G and 6G promises, significant advances in antenna and antenna array technologies must be accomplished.
1.1 5G Requirements of Antenna Arrays
One of the most important features of 5G is the employment of massive antenna arrays, with the size of the array currently varying from 64 to 128 and 256 elements. Such a large number of antenna elements in an array provide an unprecedented variety of possibilities. These include a means to increase the network capacity; the distance and data rates of individual links between the base station and mobile users; and the reduction of interference between different users and cells.
1.1.1 Array Characteristics
Generally speaking, there are three ways to exploit the benefits of antenna arrays in 5G wireless communication systems [4, 5], namely diversity, spatial multiplexing, and beamforming. These concepts are explained as follows.
- a) Diversity and Diversity Combining
It is a fact that mobile wireless communication channels typically suffer from both temporal fading and frequency fading. As a consequence, the quality of the channel varies with time and across different frequencies. Thus, the specific characteristics of the two propagation channels observed between any two pairs of transmitting and receiving antennas are usually different due to the variation in the scattering along the corresponding propagation paths. The peaks and troughs of the strength of the received signal at one antenna would be different from those at another antenna in a rich scattering environment. If the correlation between those two signals is low, one can combine them through so-called diversity combining to obtain a greater signal-to-interference-and-noise ratio (SINR). The latter is also known as diversity gain. A simple viewpoint is that diversity combining techniques aim to improve the quality of the individual links between the base stations and the user terminals by increasing the SINR.
From an antenna point of view, diversity can be obtained by exploiting either the distance between adjacent antennas, i.e., their positions, or different polarizations at the receiver and the transmitter. However, a fundamental requirement is that the mutual coupling between these diversity antennas must be low. Most modern base station antennas employ polarization diversity, i.e., each antenna element is dual-polarized typically with two pairs of slanted dipole "arms" in the ±45° directions. In 5G millimeter-wave (mm-wave) systems, for example, a popular antenna configuration is to have beamforming antenna arrays with ±45° polarizations, respectively.
- b) Spatial Multiplexing
Multiplexing is the process of combining multiple digital or analog signals into a data stream for their transmission over a common medium, thus sharing a scarce resource. Spatial multiplexing aims to establish separate data streams in parallel using the same time/frequency resources. Thus, the space dimension is reused, i.e., multiplexed.
The simplest spatial multiplexing scheme is to employ sectorized antennas, a conventional technique for frequency reuse. More advanced spatial multiplexing schemes employ spatial-temporal (or frequency) coding by virtue of multiple input and multiple output (MIMO) antennas. A MIMO system requires the use of multiple antennas at least at the base stations. MIMO is implemented with two basic schemes as described below.
The first spatial multiplexing scheme is known as single user MIMO (SU-MIMO). By virtue of multiple antennas at both the base station and the user terminals, SU-MIMO first splits the data stream transmitted toward a specific user into multiple data streams. It then recombines them together at the user terminal to improve the information throughput and system capacity. One major challenge to SU-MIMO is the need for the tightly packed multiple antennas in the terminals to be decoupled.
The second spatial multiplexing scheme is known as multiuser MIMO (MU-MIMO). MU-MIMO aims to maximize the overall data throughput between all of the users and their associated base station. While it employs an antenna array at the base station, only one or a few antenna elements are present at each user terminal. Since user terminals are typically well dispersed within a radio cell and their individual channels are likely to be uncorrelated, the benefits of MU-MIMO are easier to achieve.
Both SU-MIMO and MU-MIMO protocols are intended for implementation in most 5G systems.
- c) Beamforming
Spatial filtering can be regarded as a simple version of MU-MIMO. Beamforming achieves this spatial filtering by coherently combining the fields radiated by the array elements to direct their radiated energy into particular directions. These multiple beams are created at the base station to communicate with different users simultaneously.
Beamforming offers two benefits to a communication system. The first is capacity. If there is no overlap of the beams, simultaneous communications can take place in the same frequency band and at the same time without causing much interference. The second is the gain of the antenna array. Higher gain translates into information exchange over greater distances or higher data rates due to increased SINR values. Unlike 3G and 4G antenna arrays that provide coverage with fixed beam patterns and directivity, 5G arrays must support on-demand beam coverage according to real-time application scenarios and user distributions. Moreover, they must be able to support beam management in order to deliver precise coverage in target areas while significantly suppressing interference in other areas.
For beamforming to be effective, large antenna arrays are necessary to generate narrow beams and produce scattering from mobile users with small angular spreads. The latter is to ensure that the majority of the signals transmitted and received from a mobile platform is covered by a narrow base station antenna beam. These requirements, in conjunction with wide bandwidths, support the use of millimeter wave (mm-wave) communications for 5G. In particular, mm-waves propagate in a pseudo-light fashion so the scattering of the signals to and from a mobile platform is highly localized. Furthermore, since their wavelengths are small, an electrically large mm-wave array can be fit easily into a physically small space.
1.1.2 Frequency Bands
Another major challenge associated with 5G antenna arrays is the simultaneous support of all allotted frequency bands [6]. As the number of bands being considered to meet current and future 5G needs increases, significant antenna array innovations are required to support all of them. Moreover, existing 4G bands must be supported as well [7].
Owing to the stringent requirements placed on the radiation patterns produced by cellular systems and on the levels of their impedance matching to sources to maximize their realized gains, the mobile communication industry has so far adopted an approach of using different antennas to support different frequency bands. However, because of the limited space at base station antenna sites and in mobile platforms, the coexistence of these different antennas has posed serious challenges already. It is extremely difficult to maintain low coupling levels between antennas operating over the same band and even harder to suppress the scattering interactions between antennas that operate over different bands. The latter can cause significant distortions to the radiation patterns. It is with this background that the decoupling and de-scattering issues will be addressed in Chapters 2 and 3, respectively.
1.1.3 Component Integration and Antennas-in-Package (AiP)
Clearly, the number of...
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