![The Internet of Materials](http://img.images-bn.com/static/redesign/srcs/images/grey-box.png?v11.9.4)
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Overview
However, for non-specialists, individual metasurfaces are currently restricted to limited reusability and accessibility. This book brings together various scientific disciplines with the aim of outlining a programmable ‘plug-and-play’ metasurface.
The book focuses on a recently proposed platform – known as the HyperSurface – that provides many electromagnetic functions of metasurfaces in a single structure, which can be controlled and reconfigured by software. This revolutionary approach paves the way for new opportunities in wireless communications and programmable wireless environments: HyperSurfaces could link networks with objects and physical environments and create smarter systems that are far more responsive to user demands. Walls that absorb radiation or block digital eavesdropping, and wireless, long-distance charging of devices are among the many possibilities.
The book aspires to provide the foundational knowledge for creating an Internet of Materials, enabling smart environments at any scale – from indoor wireless communications to medical imaging equipment. Although the set of disciplines involved covers a considerable span, we hope that the material will benefit experts and students alike.
Product Details
ISBN-13: | 9780367551766 |
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Publisher: | CRC Press |
Publication date: | 12/19/2022 |
Pages: | 358 |
Product dimensions: | 6.12(w) x 9.19(h) x (d) |
About the Author
Table of Contents
PrefaceIntroduction
Electromagnetic specifications and prototype designs of Software Defined Surfaces
3.1 Electromagnetic modeling of metasurfaces
3.1.1 Unit cell, polarizability, and interaction constant
3.1.2 Impedance boundary condition
3.1.3 Sheet impedance
3.2 Metasurfaces and their functionalities compared with other sheet materials and phased array antennas
3.2.1 Sheets of usual materials
3.2.2 Antenna arrays
3.2.3 Metasurfaces
3.2.4 Comparison of possible functionalities and advantages of metasurfaces
3.3 Tunable metasurfaces: from global tuning to software-defined metasurfaces
3.3.1 Global tuning
3.3.1.1 Electric tuning
3.3.1.2 Magnetic tuning
3.3.1.3 Tuning by light
3.3.1.4 Thermal tuning
3.3.2 Local tuning
3.3.2.1 Switch diode
3.3.2.2 Continuous tuning varactors
3.3.2.3 Coding metasurfaces
3.3.3 Software-defined metasurfaces
3.4 Design workflow of the switch-fabric prototype
3.4.1 Design principles per functionality
3.4.1.1 Tunable perfect absorption
3.4.1.2 Tunable anomalous reflection
3.4.2 Proof-of-concept design and its performance
3.4.2.1 Tunable perfect absorption
3.4.2.2 Tunable anomalous reflection
3.4.3 Practical considerations and restrictions
3.4.3.1 Electronic package considerations from the EM aspect
3.4.3.2 Where should we position the package vertically
3.4.3.3 Linking electromagnetic and package designs
3.4.3.4 Basic unit-cell parameters
3.4.3.5 Advanced design considerations
3.4.4 Overview of the switch-fabric tunable absorber design
3.5 Electromagnetic performance of the switch-fabric design
3.5.1 Tunable perfect absorption
3.5.3 Polarization conversion
3.5.4 Electromagnetic characterization procedures
3.5.4.1 Experimental set up
3.5.4.2 Demonstration procedure
3.5.4.3 Spatial modulation of load configuration for better performance
3.6 Design of the graphene-based prototype
3.6.1 Practical considerations and design constraints
3.6.2 Graphene combined with metallic patches
3.6.3 Frequency-tunable perfect absorber
3.6.4 Switchable absorber
3.6.5 All-angle perfect absorber
3.7 Summary
Designing the Internet-of-materials interaction software
4.1 Software design considerations
4.2 The Internet of Materials software architecture
4.3 The Internet of Materials Application Programming Interface
4.3.1 General Use Case Diagram
4.3.2 The Database Diagram
4.3.2.1 Table “DoA”
4.3.2.2 Table “Polarities”
4.3.2.3 Table “SwitchStates”
4.3.2.4 Table “Physical Setup”
4.3.2.5 Table “Function Electromagnetic Profiles”
4.3.3 The Class Diagram
4.4 A novel software class: The Electromagnetic Compiler
4.4.1 A Qualitative view of the compiling process
4.4.2 Metasurface functions
4.4.3 Formal Definition of a Metasurface Configuration
4.4.4 Definition of Fitness function
4.4.5 Methods
4.5 Theoretical foundations of the Electromagnetic Compiler
4.5.1 Definitions
4.5.2 Floquet (unit-cell) analysis
4.5.3 ABSORB functionality
4.5.4 REFLECT functionality
4.5.5 POLARIZE functionality
4.5.6 STEER functionality
4.5.7 SPLIT functionality
4.5.8 Far-field scattering/radiation pattern
4.5.9 Formal definition
4.5.10 Semi-analytical calculation
4.5.11 Polarization
4.5.12 Scattered power in a lobe (solid angle cone)
4.5.13 Fitness functions per functionality
4.5.13.1 ABSORB functionality
4.5.13.2 STEER functionality
4.5.13.3 REFLECT functionality
4.5.13.4 SPLIT functionality
4.5.13.5 POLARIZE functionality
4.5.13.6 FOCUS and COLLIMATE functionalities
4.5.13.7 SCATTER functionality
4.5.13.8 ARBITRARY functionality
4.5.14 The configuration optimization process
4.6 Software aspects of the Electromagnetic Compiler
4.6.1 General Use Cases
4.6.2 Validating the compilation outcomes with measurements
4.7 Conclusion
Design of the HyperSurface networking aspects
5.1 Design Requirements of the Hypersurface Controller Network
5.2 Hypersurface Networking Components: The Hypersurface Network Controller
5.2.1 Hypersurface Controller Communication
5.3 The Hypersurface Controller Network Topology
5.3.1 Hypersurface Network Controller Addressing
5.3.2 Hypersurface Network Controller Channel Mapping
5.4 Hypersurface Controller Network Communication Protocols
5.4.1 Routing and Reporting Protocol
5.4.2 Fault-adaptive Routing
5.4.3 Workload Characterization
5.5 Evaluation of the Controller Network Design and Performance via Simulations
5.5.1 Custom-built Simulations
5.5.2 Hypersurface Controller Network Simulator
5.5.2.1 The Hypersurface Controller Network Simulation
5.5.3 Formal Evaluation of the HSF-CN
5.5.4 HyperSurface Emulator
5.6 The Controller-Gateway communication perspective
5.6.1 Gateway functionality
5.6.1.1 Software/Firmware Design and Development
5.6.1.2 Tile Gateway Communication Interface Firmware
5.6.1.3 Error/Fault Detection
5.6.1.4 Bluetooth Mesh Firmware
5.7 The HyperSurface within control loops
5.7.1 System Model
5.7.2 The Considered Model
5.7.3 Control Algorithm
5.7.4 Estimation Algorithm
5.7.5 Performance Evaluation
5.8 Summary
Internet of Things-compliant platforms for inter-networking metamaterials
6.1 Overview
6.2 Hardware actuation approaches
6.2.1 RF switching elements
6.2.1.1 PIN Diodes
6.2.2 Controller to PIN interface
6.2.2.1 DAC
6.3 Controller communication
6.3.1 Controller to controller communication
6.3.1.1 SPI
6.3.1.2 I2C
6.3.1.3 UART
6.3.1.4 CAN
6.3.2 Controller to Server communication
6.3.2.1 Bluetooth
6.3.2.2 802.15.4
6.3.2.3 Zigbee
6.3.2.4 UWB
6.3.2.5 LORA
6.4 Controller Hardware
6.4.1 The ESP8266/ESP32
6.4.2 Arduino
6.4.3 Raspberry PI
6.4.4 BeagleBone
6.4.5 Libelium WaspMote
6.4.6 OpenMote
6.5 IoT Operating systems
6.5.1 TinyOS
6.5.2 Contiki/Contiki-NG
6.5.3 FreeRTOS
6.5.4 Android Things
6.5.5 OpenWRT
6.5.6 Raspbian
6.5.7 OpenWSN
6.6 IoT Broker
6.6.1 MQTT brokers
6.6.1.1 Mosquitto
6.6.1.2 RabbitMQ
6.6.1.3 EMQ
6.6.1.4 VerneMQ
6.7 Conclusions
Interim: Drafting a stack
The scaling laws of HyperSurfaces
8.1 The HyperSurface Scalability versus Manufacturing Technologies
8.1.1 Scaling Model
8.1.1.1 Dimensional Factors
8.1.1.2 Programming Parameters
8.1.2 Methodology
8.1.2.1 Unit Cell Model
8.1.2.2 Metasurface Model
8.1.2.3 Metasurface Coding
8.1.2.4 Performance Metrics
8.1.2.5 Validation
8.1.3 Performance Scalability
8.1.3.1 Directivity
8.1.3.2 Target Deviation
8.1.3.3 Half Power Beam Width
8.1.3.4 Side Lobe Level
8.1.4 The HyperSurface Energy Footprint, Cost and Performance
8.1.4.1 Cost and Power Models
8.1.4.2 Application-Specific Figures of Merit
8.1.4.3 Performance-Cost Analysis
8.2 The HyperSurface Data Traffic as a Scaling Concern
8.2.1 System Model
8.2.1.1 Mobility Model
8.2.1.2 Gateway Model
8.2.1.3 Embedded Controller Network
8.2.2 Evaluation Methodology
8.2.2.1 Relevant Inputs
8.2.2.2 Traffic Analysis Metrics
8.2.2.3 Walkthrough Example
8.2.3 Workload Characterization
8.2.3.1 Spatio-temporal Intensity
8.2.3.2 Reconfiguration Delay
8.2.3.3 Sensitivity Analysis
8.2.4 Indoor Mobility Scenario
8.3 Conclusions
Applications of the Internet-of-materials: Programmable wireless environments
9.1 Deterministic wireless propagation control as a concept
9.2 Modeling, simulating and configuring PWEs - a ray-routing approach based on graph theory
9.2.1 General Modeling and Properties of HyperSurface Functions
9.2.2 Specialized Modeling of Function Inputs/Outputs
9.2.3 Modeling Core HyperSurface Functions
9.2.4 A Graph Model for Simulating and Optimizing Programmable Wireless Environments
9.2.5 Modeling connectivity objectives
9.2.5.1 Power transfer maximization
9.2.5.2 QoS optimization
9.2.5.3 Eavesdropping mitigation
9.2.5.4 Doppler effect mitigation
9.2.5.5 User blocking
9.3 A K-paths Approach for Multi-User Multi-Objective Environment Configuration
9.4 Artificial Intelligence-based configuration of PWEs
9.4.0.1 Feed-forward
9.4.0.2 Back-propagation
9.5 The novel PWE potential in Communication Quality,
Cybersecurity and Wireless Power Transfer
9.5.1 Multi-User Multi-Objective Showcase
9.5.2 Doppler Effect Mitigation Showcase
9.5.3 User Capacity and Stress test
9.5.4 Evaluation of Neural Network-based PWE heuristics
9.6 Conclusion
Epilogue