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English
Wiley-Scrivener
13 June 2025
Energy-Efficient Communication Networks is essential for anyone looking to understand and implement cutting-edge energy optimization strategies for communication systems, ensuring they meet growing energy demands while seamlessly integrating renewable energy sources and enhancing battery life in embedded applications.

Renewable energy, including solar, wind, and geothermal energy, for communication networks is a key area of exploration for meeting the demands of their increasing energy requirements. Scheduling and power cycle optimization are instrumental in deciding the effectiveness of these networks. Apart from communication, embedded systems running on batteries designed for data processing applications also face restrictions in terms of battery life—targeting low-energy consumption-based systems is particularly important here. The increased usage of sensor networks for personal and commercial applications has resulted in a surge of development to create energy-aware protocols and algorithms.

This book introduces energy optimization concepts for current and future communication networks and explains how to optimize electricity for wireless sensor networks and incorporate renewable energy sources into conventional communication networks. It gives readers a better understanding of the difficulties, limitations, and possible bottlenecks that may occur while developing a communication system under power constraints, as well as insights into the traditional and recently developed communication systems from an energy optimization point of view.
Edited by:   , , , , , ,
Imprint:   Wiley-Scrivener
Country of Publication:   United States
ISBN:   9781394271658
ISBN 10:   1394271654
Pages:   272
Publication Date:  
Audience:   Professional and scholarly ,  Undergraduate
Format:   Hardback
Publisher's Status:   Active
Preface xv List of Contributors xvii 1 Efficient Energy Management in Hyperledger Fabric Blockchain Networks: A Proposed Optimized Solution 1 Kamurthi Ravi Teja and Shakti Raj Chopra 1.1 Introduction 2 1.2 Methodology 3 1.3 Experimental Analysis 4 1.4 Results and Discussion 5 1.5 Conclusion 7 2 Framework for UAV-Based Wireless Power Harvesting 9 Tanishk Singhal and Harpreet Singh Bedi 2.1 Introduction 9 2.2 Literature Review 10 2.3 Results and Discussion 15 2.4 Conclusion 19 3 Future Generation Technology and Feasibility Assessment 23 Pradeep Singh, Krishan Arora and Umesh C. Rathore 3.1 Introduction 24 3.2 Next-Generation Electrical Technologies 26 3.3 Artificial Intelligence 37 3.4 Machine Learning 41 3.5 Conclusion 46 4 IoT-Enabled Weather Forecasting Systems in Future Networks: Constraints and Solutions 51 Yogesh Kumar Verma, Archana Kanwar and Manoj Kumar Shukla 4.1 Introduction 52 4.2 Need of IoT-Based Weather Forecasting System 53 4.3 Methodology and Results 58 4.4 Conclusion 61 5 Cognitive Radio-Based NOMA Communication Networks 65 Indu Bala 5.1 Introduction to Cognitive Radio and NOMA Networks 66 5.2 Fundamentals of Cognitive Radio Technology 67 5.3 Principles of Non-Orthogonal Multiple Access (NOMA) 70 5.4 Integration of Cognitive Radio with NOMA 73 5.5 Performance Evaluation and Analysis 77 5.6 Applications and Use Cases 78 5.7 Challenges and Future Directions 80 5.8 Conclusion 82 6 Cognitive Radio (CR) Based Non-Orthogonal Multiple Access (NOMA) Network 87 Raja Gunasekaran, Ragavi Boopathi, Gobinath Velu Kaliyannan, Dinesh Dhanabalan and Kesavan Duraisamy 6.1 Introduction 88 6.2 Fundamentals of CR 90 6.3 Spectrum Management System 96 6.4 Noma Networks 98 6.5 Enabling Technologies 104 6.6 Conclusion 107 7 Artificial Intelligence and Machine Learning-Based Network Power Optimization Schemes 115 Jyoti, Aarti Shar, Ramandeep Sandhu, Manish Kumar Sharma and Deepika Ghai 7.1 Introduction 116 7.2 Network 117 7.3 Decentralized Connection 120 7.4 Communication Network 121 7.5 Internet of Things (IoT) 123 7.6 5G and Future Technologies 123 7.7 Network Power and Unstable Power Supply of Computer Networks 123 7.8 Adaption of Optimization Schemes to Enhance Network Power 124 7.9 Related Work 127 7.10 Traditional Evaluation AI and ML-Based Network Energy Optimization Techniques 129 7.11 AI- and ML-Based Systems for Network Energy Optimization Techniques 132 7.12 Conclusion 135 8 Integration of PV Solar Rooftop Technology for Enhanced Performance and Sustainability of Electric Vehicles: A Techno-Analytical Approach 139 Vinay Anand and Himanshu Sharma 8.1 Introduction 140 8.2 Literature Review 142 8.3 Methods and Methodology 144 8.4 Result and Discussion 147 8.5 Conclusion 153 9 The Viability of Advanced Technology for Future Generations 157 Manjushree Nayak and Ashutosh Pattnaik 9.1 Introduction 158 9.2 Communication Systems 159 9.3 Conclusion 171 10 Power Optimization and Scheduling for Multi-Layer, Multi-Dimensional 6G Communication Networks 175 Harpreet Kaur Channi, Pulkit Kumar and Ramandeep Sandhu 10.1 Introduction 176 10.2 Literature Review 177 10.3 Multi-Layer, Multi-Dimensional 6G Communication Networks 180 10.4 Power Optimization in MLMD 6G Networks 183 10.5 Scheduling Strategies for MLMD 6G Networks 184 10.6 Proposed Framework 187 10.7 Challenges and Future Directions 190 10.8 Conclusion 193 11 Industry 4.0: Future Opportunities and Challenges 199 Manoj Singh Adhikari, Raju Patel, Manoj Sindhwani, Shippu Sachdeva and Suman Lata Tripathi 11.1 Introduction 200 11.2 Future Opportunities of Industrial 4.0 201 11.3 Increased Productivity and Efficiency 202 11.4 Innovation 203 11.5 Data-Driven Decision-Making 205 11.6 Supply Chain Optimization 205 11.7 Future Challenges of Industrial 4.0 206 11.8 Data Security and Privacy 207 11.9 Skills Gap and Workforce Training 208 11.10 Interoperability and Standardization 210 11.11 Ethical and Social Implications 211 11.12 Infrastructure Investment 211 11.13 Regulatory and Legal Challenges 212 11.14 Dependency on Technology 213 11.15 Conclusion 213 12 MIMO and Its Significance 217 Shahid Hamid and Shakti Raj Chopra 12.1 Introduction 218 12.2 MIMO 219 12.3 Signal Model for MIMO 221 12.4 Standard MIMO Configurations 223 12.5 Why MIMO 224 12.6 Results 225 References 227 Index 231

Shakti Raj Chopra, PhD is an associate professor at Lovely Professional University with over 18 years of academic experience. He has published over 45 research papers in international journals and conferences. Additionally, he has worked on several consultancy projects and participated in over 20 national and international webinars. His areas of interest include cognitive radio, blockchain, artificial intelligence, and machine learning. Krishan Arora, PhD is an associate professor and Head of the Department of Power Systems in the School of Electronics and Engineering at Lovely Professional University with over 16 years of academic experience. He has published over 70 research papers in international journals and conferences, organized several workshops, internships, and lectures, and participated in over 20 national and international webinars. His areas of research include electrical machines, non-conventional energy sources, load frequency control, and automatic generation control. Suman Lata Tripathi, PhD is a professor at Lovely Professional University with more than 20 years of academic experience. She has published over 74 research papers in international journals, 13 patents, two copyrights, and has authored and edited over 17 books. She also serves as a session chair, conference-steering committee member, editorial board member, and peer reviewer for international journals. Her areas of interest include microelectronics device modeling and characterization, low-power VLSI circuit design, and embedded system design. Vikram Kumar, PhD is a post-doctoral researcher and guest lecturer at the University of Calgary, Canada. He has published 82 research papers in international journals, three patents, and four copyrights. Additionally, he has presented research work in over two dozen national and international conferences and serves as an editorial board member of several journals. His areas of interest include multidisciplinary design and optimization, artificial intelligence and machine learning for numerical and engineering optimization, and information and communication technology for smart grid applications.

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