Coverart for item
The Resource Cognitive radio : an enabler for Internet of Things, S. Shanmugavel (Professor, National Engineering College, Kovilpatti, India), M.A. Bhagyaveni (Professor, College of Engineering, Guindy, Anna University, Chennai, India), R. Kalidoss (Professor, Sri Sivasubramaniya Nadar College of Engineering, Chennai, India)

Cognitive radio : an enabler for Internet of Things, S. Shanmugavel (Professor, National Engineering College, Kovilpatti, India), M.A. Bhagyaveni (Professor, College of Engineering, Guindy, Anna University, Chennai, India), R. Kalidoss (Professor, Sri Sivasubramaniya Nadar College of Engineering, Chennai, India)

Label
Cognitive radio : an enabler for Internet of Things
Title
Cognitive radio
Title remainder
an enabler for Internet of Things
Statement of responsibility
S. Shanmugavel (Professor, National Engineering College, Kovilpatti, India), M.A. Bhagyaveni (Professor, College of Engineering, Guindy, Anna University, Chennai, India), R. Kalidoss (Professor, Sri Sivasubramaniya Nadar College of Engineering, Chennai, India)
Creator
Contributor
Author
Distributor
Publisher
Subject
Genre
Language
eng
Summary
Internet of Things (IoT) deals with the interconnection of devices that can communicate with each other over the internet. Currently, several smart systems have evolved with the evolution in IoT. Cognitive Radio - an enabler for Internet of Things is a research level subject for all communication engineering students at undergraduate, post graduate and research levels. The contents of the book are designed to cover the prescribed syllabus for one semester course on the subject prescribed by universities. Concepts have been explained thoroughly in simple and lucid language. Mathematical analysis has been used wherever necessary followed by clear and lucid explanation of the findings and their implication. Key technologies presented include dynamic spectrum access, spectrum sensing techniques, IEEE 802.22 and different radio network architectures. Their role and use in the context of mobile broadband access in general is explained, giving both a high level overview and a detailed step by step explanation. The book includes a large number of diagrams, MATLAB examples, thereby enabling the readers to have a sound grasp of the concepts presented and their applications. This book is a must have resource for engineers and other professionals in the telecommunication industry working with cellular or wireless broadband technologies, helping comprehension of the process of utilization of the updated technology to enable being ahead competition
Member of
Cataloging source
CaBNVSL
http://library.link/vocab/creatorName
Shanmugavel, S
Dewey number
621.384
Illustrations
illustrations
Index
index present
LC call number
TK5103.4815
LC item number
.S53 2017eb
Nature of contents
  • dictionaries
  • bibliography
http://library.link/vocab/relatedWorkOrContributorName
  • Bhagyaveni, M. A.
  • Kalidoss, R.
  • IEEE Xplore (Online Service)
  • River Publishers
Series statement
River Publishers series in communications
http://library.link/vocab/subjectName
  • Cognitive radio networks
  • Internet of things
Label
Cognitive radio : an enabler for Internet of Things, S. Shanmugavel (Professor, National Engineering College, Kovilpatti, India), M.A. Bhagyaveni (Professor, College of Engineering, Guindy, Anna University, Chennai, India), R. Kalidoss (Professor, Sri Sivasubramaniya Nadar College of Engineering, Chennai, India)
Instantiates
Publication
Distribution
Bibliography note
Includes bibliographical references (pages 133-139) and index
Carrier category
online resource
Carrier MARC source
rdacarrier
Content category
text
Content type MARC source
rdacontent
Contents
  • Preface xi -- Acknowledgements xiii -- List of Figures xv -- List of Tables xix -- List of Abbreviations xxi -- 1 Introduction 1 -- 1.1 Features and Application of IoT 1 -- 1.2 Enabling Technologies and Protocols for IoT 3 -- 1.2.1 RFID and Near-Field Communication (NFC) 4 -- 1.2.2 M2M Technologies 5 -- 1.2.3 Naming and Addressing Schemes for IoT 6 -- 1.2.4 Data Storage and Analysis Techniques 7 -- 1.2.5 Cognitive Radio for IoT and M2M 7 -- 1.3 Requirement and Challenges of IoT 9 -- 1.3.1 Heterogeneity Issues 9 -- 1.3.2 Flexible, Dynamic and Efficient Networking and Communication 9 -- 1.3.3 Self-Organization, Re-Configurability and Automaticity 9 -- 1.3.4 Energy Efficiency 10 -- 1.3.5 Cooperative and Ambient Intelligence 10 -- 2 Software Defined Radio 13 -- 2.1 Introduction 13 -- 2.2 Definition of SDR 14 -- 2.2.1 Software Controlled Radio 14 -- 2.2.2 Software Defined Radio 14 -- 2.3 Levels of SDR 14 -- 2.4 SDRWaveform Portability 15 -- 2.5 SDR Security 16 -- 2.5.1 SDR Interoperability Testing 16 -- 2.5.2 SDR Hardware 17 -- 2.6 Software Radio Functional Architecture 18 -- 2.6.1 The Software Radio Model 18 -- 2.7 Classes of Software Defined Radio (SDR) 20 -- 2.8 Software Communications Architecture (SCA) 22 -- 2.8.1 SCA Basics 22 -- 2.8.2 COBRA 23 -- 2.8.3 SCA Compliance and Testing 23 -- 3 Cognitive Radio 25 -- 3.1 Introduction 25 -- 3.2 Understanding of Cognitive Radio 25 -- 3.3 Cognitive Radio Architecture 26 -- 3.4 Cognitive Radio Characteristics 27 -- 3.4.1 Primary and Secondary Users 28 -- 3.5 Cognitive Radio Environment 28 -- 3.6 Types of Cognitive Radios 30 -- 3.6.1 Procedural CRs 31 -- 3.6.2 Ontological CRs 31 -- 3.7 Cognitive Radio Networks 32 -- 3.7.1 Infrastructure (Centralized) CRNs 32 -- 3.7.2 Ad-hoc Mode CRNs 32 -- 3.8 How Cognitive Radio Empowers Internet of Things 33 -- 3.9 Challenges 34 -- 3.9.1 Spread Spectrum Primary Users 34 -- 3.9.2 Hidden Node/Sharing Issues 34 -- 3.9.3 Sensing Time 35 -- 3.9.4 Other Challenges 35 -- 4 Next Generation Networks 37
  • 4.1 Introduction 37 -- 4.2 Classical Hypothetical Analysis of Spectrum Sensing 38 -- 4.3 Transmitter Detection (Non-Cooperative Detection) 41 -- 4.4 Matched Filter Detection 41 -- 4.5 Energy Detection 42 -- 4.6 Cyclostationary Feature Detection 43 -- 4.7 Cooperative Detection 44 -- 4.8 Interference Based Detection 45 -- 4.9 Neyman Pearson Fusion Rule for Spectrum Sensing in Cognitive Radio 46 -- 4.10 Bayesian Approach for Spectrum Sensing 49 -- 4.11 Optimal Spectrum Sensing by Using Kullback Leibler Divergence 50 -- 4.11.1 System Model 51 -- 4.11.2 Spectrum Sensing Using KLD 52 -- 4.12 Spectrum Sensing Challenges 55 -- 5 Cognitive Radio for Upper Layers 57 -- 5.1 Spectrum Management 57 -- 5.1.1 Spectrum Analysis 57 -- 5.2 Spectrum Decision 59 -- 5.2.1 Challenges Faced by Spectrum Management 59 -- 5.3 Spectrum Mobility 61 -- 5.3.1 Spectrum Handoff 61 -- 5.4 Spectrum Mobility Challenges in xG Networks 62 -- 5.5 Spectrum Sharing 63 -- 5.6 Overview of Spectrum Sharing Techniques 64 -- 5.7 Inter-network Spectrum Sharing 66 -- 5.8 Centralized Inter-Network Spectrum Sharing 67 -- 5.9 Distributed Inter-Network Spectrum Sharing 68 -- 5.10 Challenges to Spectrum Sharing 68 -- 5.10.1 Common Control Channel (CCC) 68 -- 5.10.2 Dynamic Radio Range 69 -- 5.10.3 Spectrum Unit 69 -- 5.11 Upper Layer Issues 70 -- 5.11.1 Routing Challenges 70 -- 5.12 Transport Layer Challenges 72 -- 5.13 Cross-Layer Challenges in Spectrum Management 73 -- 5.14 Cross-Layer Challenges in Spectrum Handoff 73 -- 5.15 Cross-Layer Challenges in Spectrum Sharing 74 -- 5.16 Cross-Layer Challenges in Upper Layers 75 -- 5.17 MIMO Cognitive Radio 76 -- 6 Standards for Cognitive Radio IEEE 802.22Wireless Regional Area Network 79 -- 6.1 Introduction 79 -- 6.2 IEEE 802.22Wireless Regional Area Network 80 -- 6.2.1 Importance of IEEE 802.22 -- 80 -- 6.2.2 Topology of IEEE 802.22 -- 81 -- 6.2.3 Service Capacity and Coverage 81 -- 6.3 Physical Layer 82 -- 6.4 MAC Layer 83 -- 6.4.1 Super Frame Structure 84 -- 6.5 Sensing in IEEE 802.22
  • 85 -- 6.6 IEEE 802.22 Spectrum Measurements 86 -- 6.7 Turnaround Time Problems 87 -- 6.8 Modified Duplex Technique 88 -- 6.9 Simulation Results 89 -- 6.9.1 Representation of the Cells 89 -- 6.9.2 Performance of the Modified Duplex System 90 -- 6.9.3 Variation in the Number of Users 91 -- 6.10 Methodology for Idle Time Calculation 93 -- 6.11 CTS Interference in IEEE 802.22Wran Networks 93 -- 6.12 CTS Interfrence Mitigation in IEEE 802.22 Wran Networks 95 -- 6.12.1 System Model and Its Elements 95 -- 6.13 Interference Scenarios 97 -- 6.13.1 Desired Cell in Uplink 97 -- 6.13.2 Desired Cell in Downlink 98 -- 6.14 Location Based Duplex Scheme 99 -- 6.14.1 Mathematical Model 99 -- 6.15 Performance Analysis 101 -- 6.15.1 CDF for Varying Inner Cell Radii 103 -- 6.15.2 Variation of the Inter-Cell Distance 104 -- 6.15.3 Variation in the Number of Users 105 -- 6.15.4 Single User in the Desired Cell 106 -- 7 MATLAB Programs for Spectrum Sensing Technqiues 109 -- 7.1 Energy Detection 109 -- 7.2 Matched Filter Detection 113 -- 7.3 Cyclostationary Feature Detection 117 -- 7.4 Co-Operative Spectrum Sensing 122 -- 7.5 Introduction & Specifications of USRP 125 -- 7.6 USRP B200/B210 -- 126 -- 7.7 Experiment-Detection of Spectrum Holes Using USRP 127 -- 7.8 Experiment: Spectrum Sensing Using WARP 128 -- Bibliography 133 -- Index 141 -- About the Authors 145
Control code
9218870
Dimensions
unknown
Extent
1 PDF (xxiii, 146 pages)
Form of item
online
Governing access note
Restricted to subscribers or individual electronic text purchasers
Isbn
9788793519398
Media category
electronic
Media MARC source
isbdmedia
Other physical details
illustrations (some color).
Specific material designation
remote
System control number
  • (CaBNVSL)mat09218870
  • (IDAMS)0b0000648d19a1d4
System details
Mode of access: World Wide Web
Label
Cognitive radio : an enabler for Internet of Things, S. Shanmugavel (Professor, National Engineering College, Kovilpatti, India), M.A. Bhagyaveni (Professor, College of Engineering, Guindy, Anna University, Chennai, India), R. Kalidoss (Professor, Sri Sivasubramaniya Nadar College of Engineering, Chennai, India)
Publication
Distribution
Bibliography note
Includes bibliographical references (pages 133-139) and index
Carrier category
online resource
Carrier MARC source
rdacarrier
Content category
text
Content type MARC source
rdacontent
Contents
  • Preface xi -- Acknowledgements xiii -- List of Figures xv -- List of Tables xix -- List of Abbreviations xxi -- 1 Introduction 1 -- 1.1 Features and Application of IoT 1 -- 1.2 Enabling Technologies and Protocols for IoT 3 -- 1.2.1 RFID and Near-Field Communication (NFC) 4 -- 1.2.2 M2M Technologies 5 -- 1.2.3 Naming and Addressing Schemes for IoT 6 -- 1.2.4 Data Storage and Analysis Techniques 7 -- 1.2.5 Cognitive Radio for IoT and M2M 7 -- 1.3 Requirement and Challenges of IoT 9 -- 1.3.1 Heterogeneity Issues 9 -- 1.3.2 Flexible, Dynamic and Efficient Networking and Communication 9 -- 1.3.3 Self-Organization, Re-Configurability and Automaticity 9 -- 1.3.4 Energy Efficiency 10 -- 1.3.5 Cooperative and Ambient Intelligence 10 -- 2 Software Defined Radio 13 -- 2.1 Introduction 13 -- 2.2 Definition of SDR 14 -- 2.2.1 Software Controlled Radio 14 -- 2.2.2 Software Defined Radio 14 -- 2.3 Levels of SDR 14 -- 2.4 SDRWaveform Portability 15 -- 2.5 SDR Security 16 -- 2.5.1 SDR Interoperability Testing 16 -- 2.5.2 SDR Hardware 17 -- 2.6 Software Radio Functional Architecture 18 -- 2.6.1 The Software Radio Model 18 -- 2.7 Classes of Software Defined Radio (SDR) 20 -- 2.8 Software Communications Architecture (SCA) 22 -- 2.8.1 SCA Basics 22 -- 2.8.2 COBRA 23 -- 2.8.3 SCA Compliance and Testing 23 -- 3 Cognitive Radio 25 -- 3.1 Introduction 25 -- 3.2 Understanding of Cognitive Radio 25 -- 3.3 Cognitive Radio Architecture 26 -- 3.4 Cognitive Radio Characteristics 27 -- 3.4.1 Primary and Secondary Users 28 -- 3.5 Cognitive Radio Environment 28 -- 3.6 Types of Cognitive Radios 30 -- 3.6.1 Procedural CRs 31 -- 3.6.2 Ontological CRs 31 -- 3.7 Cognitive Radio Networks 32 -- 3.7.1 Infrastructure (Centralized) CRNs 32 -- 3.7.2 Ad-hoc Mode CRNs 32 -- 3.8 How Cognitive Radio Empowers Internet of Things 33 -- 3.9 Challenges 34 -- 3.9.1 Spread Spectrum Primary Users 34 -- 3.9.2 Hidden Node/Sharing Issues 34 -- 3.9.3 Sensing Time 35 -- 3.9.4 Other Challenges 35 -- 4 Next Generation Networks 37
  • 4.1 Introduction 37 -- 4.2 Classical Hypothetical Analysis of Spectrum Sensing 38 -- 4.3 Transmitter Detection (Non-Cooperative Detection) 41 -- 4.4 Matched Filter Detection 41 -- 4.5 Energy Detection 42 -- 4.6 Cyclostationary Feature Detection 43 -- 4.7 Cooperative Detection 44 -- 4.8 Interference Based Detection 45 -- 4.9 Neyman Pearson Fusion Rule for Spectrum Sensing in Cognitive Radio 46 -- 4.10 Bayesian Approach for Spectrum Sensing 49 -- 4.11 Optimal Spectrum Sensing by Using Kullback Leibler Divergence 50 -- 4.11.1 System Model 51 -- 4.11.2 Spectrum Sensing Using KLD 52 -- 4.12 Spectrum Sensing Challenges 55 -- 5 Cognitive Radio for Upper Layers 57 -- 5.1 Spectrum Management 57 -- 5.1.1 Spectrum Analysis 57 -- 5.2 Spectrum Decision 59 -- 5.2.1 Challenges Faced by Spectrum Management 59 -- 5.3 Spectrum Mobility 61 -- 5.3.1 Spectrum Handoff 61 -- 5.4 Spectrum Mobility Challenges in xG Networks 62 -- 5.5 Spectrum Sharing 63 -- 5.6 Overview of Spectrum Sharing Techniques 64 -- 5.7 Inter-network Spectrum Sharing 66 -- 5.8 Centralized Inter-Network Spectrum Sharing 67 -- 5.9 Distributed Inter-Network Spectrum Sharing 68 -- 5.10 Challenges to Spectrum Sharing 68 -- 5.10.1 Common Control Channel (CCC) 68 -- 5.10.2 Dynamic Radio Range 69 -- 5.10.3 Spectrum Unit 69 -- 5.11 Upper Layer Issues 70 -- 5.11.1 Routing Challenges 70 -- 5.12 Transport Layer Challenges 72 -- 5.13 Cross-Layer Challenges in Spectrum Management 73 -- 5.14 Cross-Layer Challenges in Spectrum Handoff 73 -- 5.15 Cross-Layer Challenges in Spectrum Sharing 74 -- 5.16 Cross-Layer Challenges in Upper Layers 75 -- 5.17 MIMO Cognitive Radio 76 -- 6 Standards for Cognitive Radio IEEE 802.22Wireless Regional Area Network 79 -- 6.1 Introduction 79 -- 6.2 IEEE 802.22Wireless Regional Area Network 80 -- 6.2.1 Importance of IEEE 802.22 -- 80 -- 6.2.2 Topology of IEEE 802.22 -- 81 -- 6.2.3 Service Capacity and Coverage 81 -- 6.3 Physical Layer 82 -- 6.4 MAC Layer 83 -- 6.4.1 Super Frame Structure 84 -- 6.5 Sensing in IEEE 802.22
  • 85 -- 6.6 IEEE 802.22 Spectrum Measurements 86 -- 6.7 Turnaround Time Problems 87 -- 6.8 Modified Duplex Technique 88 -- 6.9 Simulation Results 89 -- 6.9.1 Representation of the Cells 89 -- 6.9.2 Performance of the Modified Duplex System 90 -- 6.9.3 Variation in the Number of Users 91 -- 6.10 Methodology for Idle Time Calculation 93 -- 6.11 CTS Interference in IEEE 802.22Wran Networks 93 -- 6.12 CTS Interfrence Mitigation in IEEE 802.22 Wran Networks 95 -- 6.12.1 System Model and Its Elements 95 -- 6.13 Interference Scenarios 97 -- 6.13.1 Desired Cell in Uplink 97 -- 6.13.2 Desired Cell in Downlink 98 -- 6.14 Location Based Duplex Scheme 99 -- 6.14.1 Mathematical Model 99 -- 6.15 Performance Analysis 101 -- 6.15.1 CDF for Varying Inner Cell Radii 103 -- 6.15.2 Variation of the Inter-Cell Distance 104 -- 6.15.3 Variation in the Number of Users 105 -- 6.15.4 Single User in the Desired Cell 106 -- 7 MATLAB Programs for Spectrum Sensing Technqiues 109 -- 7.1 Energy Detection 109 -- 7.2 Matched Filter Detection 113 -- 7.3 Cyclostationary Feature Detection 117 -- 7.4 Co-Operative Spectrum Sensing 122 -- 7.5 Introduction & Specifications of USRP 125 -- 7.6 USRP B200/B210 -- 126 -- 7.7 Experiment-Detection of Spectrum Holes Using USRP 127 -- 7.8 Experiment: Spectrum Sensing Using WARP 128 -- Bibliography 133 -- Index 141 -- About the Authors 145
Control code
9218870
Dimensions
unknown
Extent
1 PDF (xxiii, 146 pages)
Form of item
online
Governing access note
Restricted to subscribers or individual electronic text purchasers
Isbn
9788793519398
Media category
electronic
Media MARC source
isbdmedia
Other physical details
illustrations (some color).
Specific material designation
remote
System control number
  • (CaBNVSL)mat09218870
  • (IDAMS)0b0000648d19a1d4
System details
Mode of access: World Wide Web

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