Spectrum Sharing in Cognitive Radio Networks: Towards Highly Connected Environments

Description

SPECTRUM SHARING IN COGNITIVE RADIO NETWORKS Discover the latest advances in spectrum sharing in wireless networks from two internationally recognized experts in the field Spectrum Sharing in Cognitive Radio Networks: Towards Highly Connected Environments delivers an in-depth and insightful examination of hybrid spectrum access techniques with advanced frame structures designed for efficient spectrum utilization. The accomplished authors present the energy and spectrum efficient frameworks used in high-demand distributed architectures by relying on the self-scheduled medium access control (SMC-MAC) protocol in cognitive radio networks. The book begins with an exploration of the fundamentals of recent advances in spectrum sharing techniques before moving onto advanced frame structures with spectrum accessing approaches and the role of spectrum prediction and spectrum monitoring to eliminate interference. The authors also cover spectrum mobility, interference, and spectrum management for connected environments in substantial detail. Spectrum Sharing in Cognitive Radio Networks: Towards Highly Connected Environments offers readers a recent and rational theoretical mathematical model of spectrum sharing strategies that can be used for practical simulation of future generation wireless communication technologies. It also highlights ongoing trends, revealing fresh research outcomes that will be of interest to active researchers in the area. Readers will also benefit from: An inclusive study of connected environments, 3GPP Releases, and the evolution of wireless communication generations with a discussion of advanced frame structures and access strategies in cognitive radio networksA treatment of cognitive radio networks using spectrum prediction and monitoring techniquesAn analysis of the effects of imperfect spectrum monitoring on cognitive radio networksAn exploration of spectrum mobility in cognitive radio networks using spectrum prediction and monitoring techniquesAn examination of MIMO-based CR-NOMA communication systems for spectral and interference efficient designs Perfect for senior undergraduate and graduate students in Electrical and Electronics Communication Engineering programs, Spectrum Sharing in Cognitive Radio Networks: Towards Highly Connected Environments will also earn a place in the libraries of professional engineers and researchers working in the field, whether in private industry, government, or academia. Cover Title Page Copyright Page Contents Preface Special Acknowledgements List of Acronyms List of Figures List of Tables List of Symbols Chapter 1 Introduction 1.1 Introduction 1.1.1 Connected Environments 1.1.2 Evolution of Wireless Communication 1.1.3 Third Generation Partnership Project 1.2 Cognitive Radio Technology 1.2.1 Spectrum Accessing/Sharing Techniques 1.2.1.1 Interweave Spectrum Access 1.2.1.2 Underlay Spectrum Access 1.2.1.3 Overlay Spectrum Access 1.2.1.4 Hybrid Spectrum Access 1.3 Implementation of CR Networks 1.4 Motivation 1.5 Organization of Book 1.6 Summary References Chapter 2 Advanced Frame Structures in Cognitive Radio Networks 2.1 Introduction 2.2 Related Work 2.2.1 Frame Structures 2.2.2 Spectrum Accessing Strategies 2.3 Proposed Frame Structures for HSA Technique 2.4 Analysis of Throughput and Data Loss 2.5 Simulations and Results 2.6 Summary References Chapter 3 Cognitive Radio Network with Spectrum Prediction and Monitoring Techniques 3.1 Introduction 3.2 Related Work 3.2.1 Spectrum Prediction 3.2.2 Spectrum Monitoring 3.3 System Models 3.3.1 System Model for Approach-1 3.3.2 System Model for Approach-2 3.4 Performance Analysis 3.4.1 Throughput Analysis Using Approach-1 3.4.2 Analysis of Performance Metrics of the Approach-2 3.5 Results and Discussion 3.5.1 Proposed Approach-1 3.5.2 Proposed Approach-2 3.6 Summary References Chapter 4 Effect of Spectrum Prediction on Cognitive Radio Networks 4.1 Introduction 4.1.1 Spectrum Access Techniques 4.2 System Model 4.3 Throughput Analysis 4.4 Simulation Results and Discussion 4.5 Summary References Chapter 5 Effect of Imperfect Spectrum Monitoring on Cognitive Radio Networks 5.1 Introduction 5.2 Related Work 5.2.1 Spectrum Sensing 5.2.2 Spectrum Monitoring 5.3 System Model 5.4 Performance Analysis of Proposed System Using Imperfect Spectrum Monitoring 5.4.1 Computation of Ratio of the Achieved Throughput to Data Loss 5.4.2 Computation of Power Wastage 5.4.3 Computation of Interference Efficiency 5.4.4 Computation of Energy Efficiency 5.5 Results and Discussion 5.6 Summary References Chapter 6 Cooperative Spectrum Monitoring in Homogeneous and Heterogeneous Cognitive Radio Networks 6.1 Introduction 6.2 Background 6.3 System Model 6.4 Performance Analysis of Proposed CRN 6.4.1 Computation of Achieved Throughput and Data Loss 6.4.2 Computation of Interference Efficiency 6.4.3 Computation of Energy Efficiency 6.5 Results and Discussion 6.5.1 Homogeneous Cognitive Radio Network 6.5.2 Heterogeneous Cognitive Radio Networks 6.6 Summary References Chapter 7 Spectrum Mobility in Cognitive Radio Networks Using Spectrum Prediction and Monitoring Techniques 7.1 Introduction 7.2 System Model 7.3 Performance Analysis 7.4 Results and Discussion 7.5 Summary References Chapter 8 Hybrid Self-Scheduled Multichannel Medium Access Control Protocol in Cognitive Radio Networks 8.1 Introduction 8.2 Related Work 8.2.1 CR-MAC Protocols 8.2.2 Interference at PU 8.3 System Model and Proposed Hybrid Self-Scheduled Multichannel MAC Protocol 8.3.1 System Model 8.3.2 Proposed HSMC-MAC Protocol 8.4 Performance Analysis 8.4.1 With Perfect Spectrum Sensing 8.4.2 With Imperfect Spectrum Sensing 8.4.3 More Feasible Scenarios 8.5 Simulations and Results Analysis 8.5.1 With Perfect Spectrum Sensing 8.5.2 With Imperfect Spectrum Sensing 8.6 Summary References Chapter 9 Frameworks of Non-Orthogonal Multiple Access Techniques in Cognitive Radio Networks 9.1 Introduction 9.1.1 Related Work 9.1.2 Motivation 9.1.3 Organization 9.2 CR Spectrum Accessing Strategies 9.3 Functions of NOMA System for Uplink and Downlink Scenarios 9.3.1 Downlink Scenario for Cellular-NOMA 9.3.2 Uplink Scenario for Cellular-NOMA 9.4 Proposed Frameworks of CR with NOMA 9.4.1 Framework-1 9.4.2 Framework-2 9.5 Simulation Environment and Results 9.6 Research Potentials for NOMA and CR-NOMA Implementations 9.6.1 Imperfect CSI 9.6.2 Spectrum Hand-off Management 9.6.3 Standardization 9.6.4 Less Complex and Cost-Effective Systems 9.6.5 Energy-Efficient Design and Frameworks 9.6.6 Quality-of-Experience Management 9.6.7 Power Allocation Strategy for CUs to Implement NOMA Without Interfering PU 9.6.8 Cooperative CR-NOMA 9.6.9 Interference Cancellation Techniques 9.6.10 Security Aspects in CR-NOMA 9.6.11 Role of User Clustering and Challenges 9.6.12 Wireless Power Transfer to NOMA 9.6.13 Multicell NOMA with Coordinated Multipoint Transmission 9.6.14 Multiple-Carrier NOMA 9.6.15 Cross-Layer Design 9.6.16 MIMO-NOMA-CR 9.7 Summary References Chapter 10 Performance Analysis of MIMO-Based CR-NOMA Communication Systems 10.1 Introduction 10.2 Related Work for Several Combinations of CR, NOMA, and MIMO Systems 10.3 System Model 10.3.1 Downlink Scenarios 10.3.2 Uplink Scenario 10.4 Performance Analysis 10.4.1 Downlink Scenario 10.4.1.1 Throughput Computation for MIMO-CR-NOMA 10.4.1.2 Throughput Computation for CR-NOMA Systems 10.4.1.3 Sum Throughput for CR-OMA, CR-NOMA, CR-MIMO, and CR-NOMA-MIMO Frameworks 10.4.2 Uplink Scenario 10.4.2.1 Throughput Computation for MIMO-CR-NOMA 10.4.2.2 Throughput Calculation for CR-NOMA Systems 10.4.2.3 Sum Throughput for CR-OMA, CR-NOMA, CR-MIMO, and CR-NOMA-MIMO Frameworks 10.4.2.4 Computation of Interference Efficiency of CU-4 In Case of CR-MIMO-NOMA 10.5 Simulation and Results Analysis 10.5.1 Simulation Results for Downlink Scenario 10.5.2 Simulation Results for Uplink Scenario 10.6 Summary References Chapter 11 Interference Management in Cognitive Radio Networks 11.1 Introduction 11.1.1 White space 11.1.2 Grey Spaces 11.1.3 Black Spaces 11.1.4 Interference Temperature 11.2 Interfering and Non-interfering CRN 11.2.1 Interfering CRN 11.2.2 Non-Interfering CRN 11.3 Interference Cancellation Techniques in the CRN 11.3.1 At the CU Transmitter 11.3.2 At the CR-Receiver 11.4 Cross-Layer Interference Mitigation in Cognitive Radio Networks 11.5 Interference Management in Cognitive Radio Networks via Cognitive Cycle Constituents 11.5.1 Spectrum Sensing 11.5.2 Spectrum Prediction 11.5.3 Transmission Below PUs' Interference Tolerable Limit 11.5.4 Using Advanced Encoding Techniques 11.5.5 Spectrum Monitoring 11.6 Summary References Chapter 12 Simulation Frameworks and Potential Research Challenges for Internet-of-Vehicles Networks 12.1 Introduction 12.1.1 Consumer IoT 12.1.2 Industrial IoT 12.2 Applications of CIoT 12.2.1 Smart Home and Automation 12.2.2 Smart Wearables 12.2.3 Home Security and Smart Domestics 12.2.4 Smart Farming 12.3 Applications of Industrial IoT 12.3.1 Smart Industry 12.3.2 Smart Grid/Utilities 12.3.3 Smart Communication 12.3.4 Smart City 12.3.5 Smart Energy Management 12.3.6 Smart Retail Management 12.3.7 Robotics 12.3.8 Smart Cars/Connected Vehicles 12.4 Communication Frameworks for IoVs 12.4.1 Vehicle-to-Vehicle (V2V) Communication 12.4.2 Vehicle to Infrastructure (V2I) Communication 12.4.3 Infrastructure to Vehicles (I2V) Communication 12.4.4 Vehicle-to-Broadband (V2B) Communication 12.4.5 Vehicle-to-Pedestrians (V2P) Communication 12.5 Simulation Environments for Internet-of-Vehicles 12.5.1 SUMO 12.5.2 Network Simulator (NetSim) 12.5.3 Ns-2 12.5.4 Ns-3 12.5.5 OMNeT++ 12.6 Potential Research Challenges 12.6.1 Social Challenges 12.6.2 Technical Challenges 12.7 Summary References Chapter 13 Radio Resource Management in Internet-of-Vehicles 13.1 Introduction 13.1.1 Dedicated Short-Range Communication 13.1.2 Wireless Access for Vehicular Environments 13.1.3 Communication Access for Land Mobile (CALM) 13.2 Cellular Communication 13.2.1 3GPP Releases 13.2.2 Long-Term Evolution 13.2.3 New Radio 13.2.4 Dynamic Spectrum Access 13.3 Role of Cognitive Radio for Spectrum Management 13.4 Effect of Mobile Nature of Vehicles/Nodes on the Networking 13.5 Spectrum Sharing in IoVs 13.5.1 Spectrum Sensing Scenarios 13.5.2 Spectrum Sharing Scenarios 13.5.3 Spectrum Mobility/Handoff Scenarios 13.6 Frameworks of Vehicular Networks with Cognitive Radio 13.6.1 CR-Based IoVs Networks Architecture 13.7 Key Potentials and Research Challenges 13.7.1 Key Potentials 13.7.2 Research Challenges 13.8 Summary References Index EULA