
Digital Transformation - Modernization and Optimization of Wireless Networks
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Content
- Intro
- Contents
- Preface
- Chapter 1
- An Analysis of D2D Network Modeling and Its Performance
- Abstract
- 1. Introduction
- 1.1. Literature Survey
- 1.2. Contribution
- 2. System Model for UAV-Assisted D2D Communication
- 2.1. Probability of Outage (OP) for NOMA and OMA Technique
- 2.2. Downlink Signal Transmission from , - .
- 2.3. Sum Rate (Throughput) Analysis
- 2.4. Energy Efficiency
- 2.5. Results and Discussion
- 3. System Model for D2D Communication with MIMO-NOMA
- 4. Results and Discussion
- Conclusion
- References
- Chapter 2
- Energy Minimization in the IoT Environment
- Abstract
- 1. Introduction
- 2. Literature Survey
- 3. Proposed Work
- 3.1. Drawback
- 3.2. Assumptions
- 4. Analysis of Work
- 5. Future Work
- Conclusion
- References
- Chapter 3
- A Performance Comparison of C-RS-NOMA with Different Hybrid Technologies for Future Generation Mobile Communication
- Abstract
- 1. Introduction
- 2. Literature Review
- 3. Modeling of System
- 3.1. NOMA
- 3.2. Cooperative - NOMA
- 3.3. MIMO-NOMA
- Decoding of Weak User 2
- Decoding of Strong User 1
- 3.4. C-RS-NOMA
- 4. Simulation Set-Up for the Comparison of Various Techniques
- 5. Simulation Results for Comparison
- 5.1. Channel Capacity
- 5.2. Far User (Weak User) Achievable Data Rate
- 5.3. Spectral Efficiency
- 5.4. Energy Efficiency (EE)
- 5.5. The Trade-Off between SE and EE
- 5.6. Performance Improvement in C-RS-NOMA
- Conclusion
- References
- Chapter 4
- The Application of WSN during Human Activity Detection and Identification Using a Deep Learning Approach
- Abstract
- 1. Introduction
- 1.1. HAR
- 1.2. Sensors Used
- 1.3. Techniques Used in HAR
- 1.4. Deep Learning
- 2. Literature Review
- 2.1. Supervised/Unsupervised Machine and Transfer Learning
- 2.2. Feature Extraction and Classification
- 2.3. Image Processing
- 2.4. Segmentation and Transfer Learning
- 3. Problem Statement
- 3.1. Proposed Work
- 3.2. Need for Research
- 4. Result and Discussion
- 4.1. Performance of CNN Classifiers to Human Activity Recognition
- Conclusion and Future Scope
- References
- Chapter 5
- The Design Mechanisms of Multiband Antennas from 1G to 5G: A Comprehensive Review
- Abstract
- 1. Introduction
- 1.1. Background of Multiband
- Issue
- 1.2. Motivation
- 1.3. Contribution
- 1.4. Drawback of Multiband
- 2. Basic Parameters of Designing a Multiband Antenna
- 2.1. Feeding Methods
- 2.2. Shape of Patch of Multiband Antenna
- 3. Overview of Multiband Antenna
- 3.1. Defected Ground Structure (DGS)
- DGS Development from 1G to 5G
- DGS Mechanism of Multiband
- DGS Application
- Fractal Method
- Fractal Development from 1g to 5G Application
- Fractal Mechanism of Multiband
- 3.2. Slot Technique
- Slot Development from 1G to 5G Generation
- Slot Mechanism
- 3.3. Reconfigurable Antenna
- The Technique Used for Reconfigurable 1G, 2G, 3G, 4G, and 5G
- Conclusion
- References
- Chapter 6
- Reconfigurable Wearable Antennas and IOT
- Abstract
- 1. Introduction
- 1.1. Wearable Antennas
- 1.2. Frequency Bands Used in Wearable Antennas
- 1.3. Factors Influencing the Performance of Wearable Antenna
- 1.4. Antenna Design Requirements for Wearable Antennas
- 1.5. Procedure for Flexible Antenna Design
- 1.6. Fabrication Steps of Wearable Antennas
- 2. Design Example of Reconfigurable Wearable Antenna
- 3. Simulation Results of Reconfigurable Wearable Antenna
- 4. IOT Basics and Antennas
- 4.1. Types of Products in IOT
- 4.2. Antenna Design Requirements in IOT
- 4.3. IOT Applications
- 4.3.1. Living IOT
- 4.3.2. Smart Agriculture - Greenhouse
- Conclusion
- References
- Chapter 7
- The Performance Enhancement of the SWIPT-NOMA Technique for 5G Wireless Networks
- Abstract
- 1. Introduction
- 2. Related Work
- 3. System Model for Swipt-Mimo-Noma
- 3.1. Proposed SWIPT-MIMO-NOMA
- 4. Simulation Setup
- 5. Simulation Results
- 5.1. Capacity
- 5.2. Outage Probability
- 5.3. Energy Efficiency
- 5.4. Spectral Efficiency
- Conclusion
- References
- Chapter 8
- How IoT Is Improving Modern Agriculture through Network Technologies
- Abstract
- 1. Introduction
- 2. IoT Based Technologies Being Used in Agriculture
- 2.1. Cloud Computing
- 2.2. Big Data Storage and Analytics
- 2.3. Robots
- 2.4. Temperature and Moisture Sensors
- 2.5. Aerial Images
- 2.6. GPS Technology
- 3. Applications of IoT in Agriculture
- 3.1. Data Collection by Smart Sensors
- 3.2. Drones are Becoming Helpers in Agriculture
- 3.3. Tracking of Stock
- 3.4. Smart Greenhouses
- 3.5. Reduce Time and Cost
- 3.6. Prediction in Smart Farming
- 4. Issues and Challenges in IoT-Based Agriculture
- 4.1. Challenges Faced by Farmers in Adopting IoT for Agriculture
- 4.1.1. Lack of Infrastructure
- 4.1.2. High Cost
- 4.1.3. Lack of Security
- 5. A Comparative Study to Know How IoT-Based Technological Devices Are Useful for Modern Agriculture
- Conclusion
- References
- Chapter 9
- Investigating Routing Issues in WSN for Smart Cities
- Abstract
- 1. Introduction
- 1.1. Machine Learning
- 1.1.1. A Glance at AI, ML, and Deep Learning
- 1.2. Wireless Sensor Network
- 1.3. Routing Protocols
- 1.4. Smart Cities
- 1.5. Role of Routing in Smart Cities
- 1.6. Organization
- 2. Literature Review
- 3. Routing
- 3.1. Routing Protocol Classification
- 3.2. Challenges for Existing Routing Protocols
- 3.3. Parameters for Performance
- 3.4. Performance Metrics with Formula
- Throughput
- Delay
- Packet Delivery Ratio
- 4. Proposed Work
- Conclusion
- Future Scope of Research
- References
- Index
- About the Editors
- Blank Page
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