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E-raamat: Spectrum Sharing in Cognitive Radio Networks: Towards Highly Connected Environments

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  • Formaat: PDF+DRM
  • Ilmumisaeg: 25-May-2021
  • Kirjastus: John Wiley & Sons Inc
  • Keel: eng
  • ISBN-13: 9781119665434
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Spectrum Sharing in Cognitive Radio Networks: Towards Highly Connected EnvironmentsSuurem pilt
  • Formaat: PDF+DRM
  • Ilmumisaeg: 25-May-2021
  • Kirjastus: John Wiley & Sons Inc
  • Keel: eng
  • ISBN-13: 9781119665434
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"The wireless communication world exemplifies the swift transformation towards 5th generation cellular networks, the rapid shift from user-centric to device-centric communication which has created a tremendous impact on service complexity and network requirements. The forthcoming networks present essential demand of ubiquitous throughput, low-latency, and high-reliability and are also intended to provide energy efficiency, spectrum reuse, network scalability, and robustness as well as improved quality ofuser experience, which proves to be of ultimate importance. Therefore, the government, academic, and industrial institutions are working together to fulfil these challenging issues"--

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 networks
  • A treatment of cognitive radio networks using spectrum prediction and monitoring techniques
  • An analysis of the effects of imperfect spectrum monitoring on cognitive radio networks
  • An exploration of spectrum mobility in cognitive radio networks using spectrum prediction and monitoring techniques
  • An 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.

Preface xiii
Special Acknowledgements xxi
List of Acronyms
xxiii
List of Figures
xxvii
List of Tables
xxxiii
List of Symbols
xxxv
1 Introduction
1(38)
1.1 Introduction
1(9)
1.1.1 Connected Environments
2(3)
1.1.2 Evolution of Wireless Communication
5(5)
1.1.3 Third Generation Partnership Project
10(1)
1.2 Cognitive Radio Technology
10(10)
1.2.1 Spectrum Accessing/Sharing Techniques
13(1)
1.2.1.1 Interweave Spectrum Access
14(3)
1.2.1.2 Underlay Spectrum Access
17(1)
1.2.1.3 Overlay Spectrum Access
17(1)
1.2.1.4 Hybrid Spectrum Access
17(3)
1.3 Implementation of CR Networks
20(2)
1.4 Motivation
22(1)
1.5 Organization of Book
23(4)
1.6 Summary
27(12)
References
27(12)
2 Advanced Frame Structures in Cognitive Radio Networks
39(16)
2.1 Introduction
39(1)
2.2 Related Work
40(3)
2.2.1 Frame Structures
40(1)
2.2.2 Spectrum Accessing Strategies
41(2)
2.3 Proposed Frame Structures for HSA Technique
43(2)
2.4 Analysis of Throughput and Data Loss
45(2)
2.5 Simulations and Results
47(3)
2.6 Summary
50(5)
References
51(4)
3 Cognitive Radio Network with Spectrum Prediction and Monitoring Techniques
55(22)
3.1 Introduction
55(2)
3.2 Related Work
57(2)
3.2.1 Spectrum Prediction
57(1)
3.2.2 Spectrum Monitoring
58(1)
3.3 System Models
59(2)
3.3.1 System Model for Approach-1
59(1)
3.3.2 System Model for Approach-2
60(1)
3.4 Performance Analysis
61(6)
3.4.1 Throughput Analysis Using Approach-1
61(4)
3.4.2 Analysis of Performance Metrics of the Approach-2
65(2)
3.5 Results and Discussion
67(5)
3.5.1 Proposed Approach-1
67(2)
3.5.2 Proposed Approach-2
69(3)
3.6 Summary
72(5)
References
72(5)
4 Effect of Spectrum Prediction on Cognitive Radio Networks
77(20)
4.1 Introduction
77(3)
4.1.1 Spectrum Access Techniques
78(2)
4.2 System Model
80(6)
4.3 Throughput Analysis
86(2)
4.4 Simulation Results and Discussion
88(5)
4.5 Summary
93(4)
References
93(4)
5 Effect of Imperfect Spectrum Monitoring on Cognitive Radio Networks
97(24)
5.1 Introduction
97(2)
5.2 Related Work
99(2)
5.2.1 Spectrum Sensing
99(1)
5.2.2 Spectrum Monitoring
100(1)
5.3 System Model
101(1)
5.4 Performance Analysis of Proposed System Using Imperfect Spectrum Monitoring
102(8)
5.4.1 Computation of Ratio of the Achieved Throughput to Data Loss
108(1)
5.4.2 Computation of Power Wastage
108(1)
5.4.3 Computation of Interference Efficiency
109(1)
5.4.4 Computation of Energy Efficiency
109(1)
5.5 Results and Discussion
110(5)
5.6 Summary
115(6)
References
116(5)
6 Cooperative Spectrum Monitoring in Homogeneous and Heterogeneous Cognitive Radio Networks
121(26)
6.1 Introduction
121(1)
6.2 Background
122(2)
6.3 System Model
124(2)
6.4 Performance Analysis of Proposed CRN
126(6)
6.4.1 Computation of Achieved Throughput and Data Loss
130(1)
6.4.2 Computation of Interference Efficiency
131(1)
6.4.3 Computation of Energy Efficiency
131(1)
6.5 Results and Discussion
132(11)
6.5.1 Homogeneous Cognitive Radio Network
132(2)
6.5.2 Heterogeneous Cognitive Radio Networks
134(9)
6.6 Summary
143(4)
References
143(4)
7 Spectrum Mobility in Cognitive Radio Networks Using Spectrum Prediction and Monitoring Techniques
147(20)
7.1 Introduction
147(4)
7.2 System Model
151(2)
7.3 Performance Analysis
153(3)
7.4 Results and Discussion
156(6)
7.5 Summary
162(5)
References
163(4)
8 Hybrid Self-Scheduled Multichannel Medium Access Control Protocol in Cognitive Radio Networks
167(28)
8.1 Introduction
167(2)
8.2 Related Work
169(3)
8.2.1 CR-MAC Protocols
169(2)
8.2.2 Interference at PU
171(1)
8.3 System Model and Proposed Hybrid Self-Scheduled Multichannel MAC Protocol
172(2)
8.3.1 System Model
172(1)
8.3.2 Proposed HSMC-MAC Protocol
173(1)
8.4 Performance Analysis
174(8)
8.4.1 With Perfect Spectrum Sensing
176(2)
8.4.2 With Imperfect Spectrum Sensing
178(2)
8.4.3 More Feasible Scenarios
180(2)
8.5 Simulations and Results Analysis
182(8)
8.5.1 With Perfect Spectrum Sensing
182(3)
8.5.2 With Imperfect Spectrum Sensing
185(5)
8.6 Summary
190(5)
References
190(5)
9 Frameworks of Non-Orthogonal Multiple Access Techniques in Cognitive Radio Networks
195(34)
9.1 Introduction
195(4)
9.1.1 Related Work
196(3)
9.1.2 Motivation
199(1)
9.1.3 Organization
199(1)
9.2 CR Spectrum Accessing Strategies
199(5)
9.3 Functions of NOMA System for Uplink and Downlink Scenarios
204(5)
9.3.1 Downlink Scenario for Cellular-NOMA
204(3)
9.3.2 Uplink Scenario for Cellular-NOMA
207(2)
9.4 Proposed Frameworks of CR with NOMA
209(3)
9.4.1 Framework-1
209(1)
9.4.2 Framework-2
210(2)
9.5 Simulation Environment and Results
212(2)
9.6 Research Potentials for NOMA and CR-NOMA Implementations
214(9)
9.6.1 Imperfect CSI
214(1)
9.6.2 Spectrum Hand-off Management
215(1)
9.6.3 Standardization
216(1)
9.6.4 Less Complex and Cost-Effective Systems
216(1)
9.6.5 Energy-Efficient Design and Frameworks
216(1)
9.6.6 Quality-of-Experience Management
217(1)
9.6.7 Power Allocation Strategy for CUs to Implement NOMA Without Interfering PU
217(1)
9.6.8 Cooperative CR-NOMA
218(1)
9.6.9 Interference Cancellation Techniques
218(1)
9.6.10 Security Aspects in CR-NOMA
218(1)
9.6.11 Role of User Clustering and Challenges
219(1)
9.6.12 Wireless Power Transfer to NOMA
220(1)
9.6.13 Multicell NOMA with Coordinated Multipoint Transmission
221(1)
9.6.14 Multiple-Carrier NOMA
221(1)
9.6.15 Cross-Layer Design
222(1)
9.6.16 MIMO-NOMA-CR
222(1)
9.7 Summary
223(6)
References
223(6)
10 Performance Analysis of MIMO-Based CR-NOMA Communication Systems
229(26)
10.1 Introduction
229(2)
10.2 Related Work for Several Combinations of CR, NOMA, and MIMO Systems
231(3)
10.3 System Model
234(4)
10.3.1 Downlink Scenarios
236(2)
10.3.2 Uplink Scenario
238(1)
10.4 Performance Analysis
238(5)
10.4.1 Downlink Scenario
238(1)
10.4.1.1 Throughput Computation for MIMO-CR-NOMA
239(1)
10.4.1.2 Throughput Computation for CR-NOMA Systems
240(1)
10.4.1.3 Sum Throughput for CR-OMA, CR-NOMA, CR-MIMO, and CR-NOMA-MIMO Frameworks
240(1)
10.4.2 Uplink Scenario
241(1)
10.4.2.1 Throughput Computation for MIMO-CR-NOMA
241(1)
10.4.2.2 Throughput Calculation for CR-NOMA Systems
242(1)
10.4.2.3 Sum Throughput for CR-OMA, CR-NOMA, CR-MIMO, and CR-NOMA-MIMO Frameworks
242(1)
10.4.2.4 Computation of Interference Efficiency of CU-4 In Case of CR-MIMO-NOMA
243(1)
10.5 Simulation and Results Analysis
243(6)
10.5.1 Simulation Results for Downlink Scenario
243(2)
10.5.2 Simulation Results for Uplink Scenario
245(4)
10.6 Summary
249(6)
References
250(5)
11 Interference Management in Cognitive Radio Networks
255(26)
11.1 Introduction
255(3)
11.1.1 White space
257(1)
11.1.2 Grey Spaces
257(1)
11.1.3 Black Spaces
257(1)
11.1.4 Interference Temperature
257(1)
11.2 Interfering and Non-interfering CRN
258(3)
11.2.1 Interfering CRN
258(1)
11.2.2 Non-Interfering CRN
259(2)
11.3 Interference Cancellation Techniques in the CRN
261(7)
11.3.1 At the CU Transmitter
261(3)
11.3.2 At the CR-Receiver
264(4)
11.4 Cross-Layer Interference Mitigation in Cognitive Radio Networks
268(1)
11.5 Interference Management in Cognitive Radio Networks via Cognitive Cycle Constituents
269(5)
11.5.1 Spectrum Sensing
269(1)
11.5.2 Spectrum Prediction
269(2)
11.5.3 Transmission Below PUs' Interference Tolerable Limit
271(1)
11.5.4 Using Advanced Encoding Techniques
271(1)
11.5.5 Spectrum Monitoring
272(2)
11.6 Summary
274(7)
References
274(7)
12 Simulation Frameworks and Potential Research Challenges for Internet-of-Vehicles Networks
281(30)
12.1 Introduction
281(3)
12.1.1 Consumer IoT
284(1)
12.1.2 Industrial IoT
284(1)
12.2 Applications of CIoT
284(2)
12.2.1 Smart Home and Automation
285(1)
12.2.2 Smart Wearables
285(1)
12.2.3 Home Security and Smart Domestics
285(1)
12.2.4 Smart Farming
286(1)
12.3 Applications of Industrial IoT
286(4)
12.3.1 Smart Industry
286(1)
12.3.2 Smart Grid/Utilities
287(1)
12.3.3 Smart Communication
287(1)
12.3.4 Smart City
288(1)
12.3.5 Smart Energy Management
288(1)
12.3.6 Smart Retail Management
289(1)
12.3.7 Robotics
289(1)
12.3.8 Smart Cars/Connected Vehicles
290(1)
12.4 Communication Frameworks for IoVs
290(5)
12.4.1 Vehicle-to-Vehicle (V2V) Communication
292(1)
12.4.2 Vehicle to Infrastructure (V2I) Communication
293(1)
12.4.3 Infrastructure to Vehicles (I2V) Communication
294(1)
12.4.4 Vehicle-to-Broadband (V2B) Communication
294(1)
12.4.5 Vehicle-to-Pedestrians (V2P) Communication
294(1)
12.5 Simulation Environments for Internet-of-Vehicles
295(4)
12.5.1 SUMO
296(1)
12.5.2 Network Simulator (NetSim)
297(1)
12.5.3 Ns-2
298(1)
12.5.4 Ns-3
298(1)
12.5.5 OMNeT++
298(1)
12.6 Potential Research Challenges
299(4)
12.6.1 Social Challenges
300(1)
12.6.2 Technical Challenges
300(3)
12.7 Summary
303(8)
References
303(8)
13 Radio Resource Management in Internet-of-Vehicles
311(28)
13.1 Introduction
311(4)
13.1.1 Dedicated Short-Range Communication
313(1)
13.1.2 Wireless Access for Vehicular Environments
314(1)
13.1.3 Communication Access for Land Mobile (CALM)
314(1)
13.2 Cellular Communication
315(4)
13.2.1 3GPP Releases
315(2)
13.2.2 Long-Term Evolution
317(1)
13.2.3 New Radio
317(1)
13.2.4 Dynamic Spectrum Access
318(1)
13.3 Role of Cognitive Radio for Spectrum Management
319(1)
13.4 Effect of Mobile Nature of Vehicles/Nodes on the Networking
320(2)
13.5 Spectrum Sharing in IoVs
322(4)
13.5.1 Spectrum Sensing Scenarios
322(2)
13.5.2 Spectrum Sharing Scenarios
324(1)
13.5.3 Spectrum Mobility/Handoff Scenarios
325(1)
13.6 Frameworks of Vehicular Networks with Cognitive Radio
326(2)
13.6.1 CR-Based IoVs Networks Architecture
327(1)
13.7 Key Potentials and Research Challenges
328(6)
13.7.1 Key Potentials
328(2)
13.7.2 Research Challenges
330(4)
13.8 Summary
334(5)
References
334(5)
Index 339
Prabhat Thakur, PhD, is a Post-Doctoral Researcher in the Department of Electrical and Electronics Engineering Science, Faculty of Engineering and the Built Environment at the University of Johannesburg, South Africa. His research focus is on the energy, spectral, and interference efficient designs for spectrum sharing in cognitive radio communication systems. 

Ghanshyam Singh, PhD, is Professor with the Department of Electrical and Electronics Engineering Science, APK Campus, at the University of Johannesburg, South Africa. He has authored or co-authored over 250 scientific papers. 
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