Microwave Devices and Circuits for Advanced Wireless Communication: Design and Analysis

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Contents
About the Editors
List of Contributors
Chapter 1 Design and Analysis of UWB Patch Antenna for 5G Millimeter Wave Applications
	1.1 Introduction
		1.1.1 Motivation for UWB Antenna Design
	1.2 Literature Survey
	1.3 Antenna Design Procedure and Methodology
	1.4 Analysis of Antennas and Findings
	1.5 Conclusion
	References
Chapter 2 Material Characterization of Graphene-Based Circular Patch Terahertz (THz) Antenna for Biomedical Applications
	2.1 Introduction
	2.2 Graphene-Based Patch Antenna Design and Analysis
	2.3 Single Input Single Output (SISO) Antenna Layout and Analysis
	2.4 Result and Discussion
	2.5 Conclusion
	References
Chapter 3 Various Mutual Coupling Reduction Techniques for 5G: MIMO Antenna
	3.1 Introduction
	3.2 What Is MIMO?
	3.3 MIMO Applications
	3.4 Mutual Coupling in MIMO
	3.5 Mutual Coupling Mechanism
		3.5.1 Mutual Coupling in the Transmitting Side
		3.5.2 Mutual Coupling in the Receiving Side
	3.6 Performance Metrics of MIMO Antenna
		3.6.1 Reflection Coefficient (S11) and VSWR
		3.6.2 Envelope Correlation Coefficient
		3.6.3 Diversity Gain
		3.6.4 Total Active Reflection Coefficient
		3.6.5 Mean Effective Gain
		3.6.6 Spectral Efficiency
		3.6.7 Channel Capacity
	3.7 Mutual Coupling Reduction Techniques
		3.7.1 Diversity Techniques
		3.7.2 Defected Ground Structure
		3.7.3 Neutralization Line Approach
		3.7.4 Electromagnetic Band Gap Structure (EBG)
		3.7.5 Parasitic Element Method
		3.7.6 SRR/CSRR Approach
	3.8 Conclusion
	References
Chapter 4 Design and Simulation Study of Bi-Frequency and Dual-Band Magnetically Insulated Line Oscillator (MILO)
	4.1 Introduction
	4.2 Design Procedure of Bi-Frequency MILO
	4.3 Analysis
	4.4 PIC Simulation of Different Bi-Frequency MILO
		4.4.1 S-Band Bi-Frequency MILO
		4.4.2 S/Ku Dual-Band MILO
	4.5 Conclusion
	References
Chapter 5 Microwave and Millimeter-Wave Radar Imaging: Challenges and Applications
	5.1 Introduction
	5.2 Fundamentals of Microwave and Millimeter Imaging
	5.3 Techniques for Image Reconstruction
		5.3.1 Diffraction Tomographic
		5.3.2 3-D Beamforming
		5.3.3 Compressed Sensing
	5.4 Different Technologies Based on MMW and Microwave Imaging, Their Uses and Challenges
		5.4.1 Through the Wall Imaging
		5.4.2 Ground Penetrating Radar
		5.4.3 Microwave Imaging in Biomedical Field
		5.4.4 Non-Destructive Testing in Industry
	5.5 Conclusions
	References
Chapter 6 High Isolation and Low RCS Tunable Wide Band Graphene-Based THz MIMO Antenna for Nano Communication with 6G/IOT Application
	6.1 Introduction
	6.2 Graphene Conductivity
	6.3 Metasurface Design Procedure and Result Discussion
	6.4 Metasurface Simulated Results
	6.5 Antenna Design
	6.6 Simulated Co-Cross-Polarization of Proposed Antenna
	6.7 Diversity Measures for the Proposed Antenna
	6.8 E- and H-Field and Surface Current and Simulated Results Discussion of Proposed Hexagonal MIMO Antenna
	6.9 Antenna with Metasurface
	6.10 Conclusion
	References
Chapter 7 Frequency Selective Surfaces/Metasurfaces: Equivalent Circuit Modelling
	7.1 Introduction
	7.2 FSS Modelling
		7.2.1 The Averaged Modelling Technique (D << λg) (Quasi-Static Regime)
		7.2.2 First Order Retrieving Method (D ≈ λg)
		7.2.3 Multimode Approach (D >> λg)
	7.3 Equivalent Circuits for Generic FSSs
	7.4 Equivalent Circuit Modelling of Dual and Multiband Metasurfaces
	7.5 Equivalent Circuit Modelling of Anisotropic FSSs
	7.6 FSS Modelling Using Coupled Line Theory
	7.7 Equivalent Circuit Modelling of Coupled Complementary Metasurfaces
	7.8 Conclusion
	References
Chapter 8 Miniaturized X Band DMTL Phase Shifter Using Space Filling Curves
	8.1 Introduction
	8.2 X Band Distributed Micro Electromechanical Transmission Line (DMTL) Phase Shifters
	8.3 Space Filling Curve
	8.4 Design and Simulation of an X Band Phase Shifter
		8.4.1 Design of a Unit Cell
		8.4.2 Design of a Phase Shifter Using Conventional CPW
		8.4.3 Design of a Phase Shifter Using Peano Space Filling Curve
		8.4.4 Design of a Phase Shifter Using Hilbert Space Filling Curve
	8.5 Conclusion
	References
Chapter 9 Microwave Devices and Circuits for Advanced Wireless Communication: Design and Analysis
	9.1 Introduction
		9.1.1 Metasurface
		9.1.2 Metasurface Antenna
		9.1.3 Different Metasurface Antenna Prototypes
	9.2 Design Analysis of the Single-Layered Metasurface Antenna
		9.2.1 Geometry of Antenna
	9.3 Design Analysis of the Multi-Layered Metasurface Antenna
		9.3.1 Antenna Design with a Radiating Element above the Metasurface
		9.3.2 Antenna Design with a Radiating Element above the Metasurface
	9.4 Conclusion
	References
Chapter 10 Design of a mmWave Reconfigurable Intelligent Surface for Futuristic Wireless Communications
	10.1 Introduction
	10.2 RIS Fundamentals
	10.3 RIS Applications
	10.4 Challenges and Research Directions
	10.5 RIS Unit Cell Design: A Case Study
	10.6 Simulation Results and Biasing Technique
		10.6.1 Biasing Model Using Arduino
	10.7 Conclusion
	Acknowledgments
	References
Chapter 11 Design of Four Element Multi-Band MIMO Antenna for 6G mmWave Wireless Applications
	11.1 Introduction
	11.2 Proposed Antenna Design
	11.3 Results and Discussion
	11.4 Conclusion
	References
Chapter 12 Intelligent Reflecting Surface Assisted D2D Communication at mm-Wave Band
	12.1 Introduction
		12.1.1 D2D Communication
		12.1.2 Intelligent Reflecting Surface
		12.1.3 Mm-Wave Network
	12.2 Standardization
		12.2.1 D2D Communication
		12.2.2 IRS
	12.3 Taxonomy of D2D Communication
	12.4 IRS Fundamentals
		12.4.1 Structure
		12.4.2 Salient Features
	12.5 Application of IRS to D2D Communication: Challenges and Solutions
		12.5.1 Resource Allocation
		12.5.2 Interference Management
		12.5.3 Power Management
	12.6 Implementation of IRS
	12.7 Potential Research Directions
	12.8 Conclusion
	References
Chapter 13 Machine Learning for Advanced Wireless Communication: Applications, Challenges, Problems, and Open Research Questions
	13.1 Introduction
		13.1.1 The Contribution of the Chapter
		13.1.2 The Organization of the Chapter
	13.2 Overview of Machine Learning in Wireless Communication
	13.3 Machine Learning Techniques for Signal Processing
		13.3.1 Denoising
		13.3.2 Equalization
		13.3.3 Modulation Recognition
		13.3.4 Feature Extraction
		13.3.5 Time Series Prediction
		13.3.6 Sparse Signal Recovery
		13.3.7 Real-Time Signal Processing and Edge Computing
		13.3.8 Cross-Modal Signal Processing
	13.4 Applications of Machine Learning in Channel Estimation
		13.4.1 Adaptive Channel Estimation
		13.4.2 Non-Linear Channel Estimation
		13.4.3 Time-Variant Channel Estimation
		13.4.4 Multi-User MIMO Channel Estimation
		13.4.5 Low-SNR Channel Estimation
		13.4.6 Channel Estimation with Limited Feedback
		13.4.7 Hybrid Beamforming Channel Estimation
		13.4.8 Interference Management
		13.4.9 Spectrum Sensing
		13.4.10 Resource Allocation and Beamforming
	13.5 Deep Learning and Neural Network Applications in Wireless Communication
		13.5.1 Modulation Classification
		13.5.2 Channel Estimation
		13.5.3 Signal Denoising and Enhancement
		13.5.4 Beamforming and Antenna Array Optimization
		13.5.5 Network Optimization and Resource Allocation
		13.5.6 Spectrum Sensing and Dynamic Spectrum Access
		13.5.7 Wireless Channel Prediction
		13.5.8 MIMO Detection and Decoding
		13.5.9 Interference Mitigation and Self-Interference Cancellation
		13.5.10 Radio Environment Mapping
		13.5.11 Localization and Positioning
		13.5.12 Dynamic Channel Selection
		13.5.13 Automatic Gain Control and Power Control
		13.5.14 Energy-Efficient Communication
	13.6 Cross-Domain Approaches: Wireless and Networking
		13.6.1 Machine Learning and Wireless
		13.6.2 Networking and Software-Defined Networking (SDN)
		13.6.3 Cloud Computing and Edge Computing
		13.6.4 Security and Privacy in Wireless Networks
		13.6.5 Wireless Sensing and the Internet of Things
		13.6.6 Green Networking and Sustainable Wireless Communication
		13.6.7 Wireless and Internet of Things Analytics
		13.6.8 Wireless and Blockchain Technology
		13.6.9 Wireless and Augmented/Virtual Reality
		13.6.10 Wireless and Renewable Energy Integration
		13.6.11 Wireless and Artificial Intelligence for Network Optimization
		13.6.12 Wireless and Big Data Analytics
		13.6.13 Wireless and Edge Intelligence
	13.7 Challenges, Problems, and Open Research Questions
		13.7.1 Challenges and Problems
		13.7.2 Open Research Questions
	13.8 Lessons Learned and Conclusion
		13.8.1 Lessons Learned from the Chapter
		13.8.2 Conclusion
	References
Chapter 14 Estimation of Channel for Multipath Transmission in Wireless Communication Using OFDM
	14.1 Introduction
	14.2 Orthogonal Frequency Division Multiplexing (OFDM)
		14.2.1 Estimation of OFDM Channel Using Singular Value Decomposition
	14.3 Estimation of Channel in OFDM
		14.3.1 A Simple Method for Multi Antenna OFDM System
		14.3.2 Data Transmission over Fading Channel by Multiple Antenna System
		14.3.3 Channel Model and Optimal Training Sequences
		14.3.4 Pilot arrangement Based Estimation of Channel in OFDM Systems
		14.3.5 Interpolation Techniques for Comb-Type Pilot Arrangement
	14.4 Grand Challenges and Opportunities for Wireless Communication
		14.4.1 Security, Secrecy, and Privacy
		14.4.2 Communication Infrastructure
		14.4.3 Coding and Modulation
	14.5 Conclusion
	References
Chapter 15 Industrial IoT: Challenges and Applications
	15.1 Introduction to IIOT
	15.2 Architecture in IIOT
	15.3 Components of IIOT Architecture
		15.3.1 IIOT Enabled Devices
		15.3.2 Management of Edge Data
		15.3.3 Cloud Processing
		15.3.4 Gateways
		15.3.5 IIOT Platforms
	15.4 Challenges in IIOT
	15.5 Automation Trends in IIOT
	15.6 Security in IIOT
	15.7 Intrusion Detection in Data Streaming, Data Analytics
	15.8 Real-Time Examples
	References
Chapter 16 Establishing Seamless Connectivity through UAV Communication Systems
	16.1 Introduction
		16.1.1 UAV Communication Systems Overview
		16.1.2 Essential Aspect of Seamless Connectivity
		16.1.3 UAV Communication System Components
		16.1.4 UAVs and Onboard Communication Systems
		16.1.5 Ground Control Station (GCS)
		16.1.6 Communication Links
	16.2 Challenges with UAV Communication Systems
		16.2.1 Limited Bandwidth
		16.2.2 Signal Interference
		16.2.3 Range and Endurance
		16.2.4 Security and Privacy
	16.3 Enhancement in UAV Communication Systems
		16.3.1 Cognitive Radio Technology
		16.3.2 Software-Defined Radio (SDR)
		16.3.3 5G and Beyond
		16.3.4 Mesh Networking
	16.4 UAV Communication Protocols
		16.4.1 Wireless Communication Protocols
		16.4.2 Protocol Stack for UAV Communication
		16.4.3 Adaptive Protocols for UAV Communication
	16.5 Antenna Systems for UAV Communication
		16.5.1 Types of Antennas for UAVs
		16.5.2 Antenna Placement and Design Considerations
	16.6 UAV Communication Networks
		16.6.1 Ad Hoc Networks for UAV Communication
		16.6.2 Hybrid Networks for UAV Communication
	16.7 Security and Privacy in UAV Communication Systems
		16.7.1 Encryption and Authentication
		16.7.2 Key Management in UAV Communication
		16.7.3 Countermeasures against Cyber Attacks
	16.8 Case Studies: Applications of UAV Communication Systems
		16.8.1 Military and Defense
		16.8.2 Search and Rescue Operations
		16.8.3 Disaster Management
	16.9 Future Trends and Challenges
		16.9.1 Integration with Internet of Things (IoT)
		16.9.2 Artificial Intelligence (AI) in UAV Communication
		16.9.3 Spectrum Management and Regulations
		16.9.4 Ethical and Legal Considerations
	16.10 Conclusion
	References
Index