Channel Aggregation and Fragmentation for Traffic Flows (eBook)
XV, 92 Seiten
Springer International Publishing (Verlag)
978-3-030-33080-4 (ISBN)
Lei Jiao obtained his Ph.D. degree in Information and Communication Technology (ICT) from the University of Agder (UiA), Norway, in 2012. He is currently an Associate Professor with the Department of ICT in UiA. He is responsible for several courses in Bachelor and Master level, such as signal processing and access in wireless networks. His research interests include modeling of stochastic process, performance evaluations of communication systems, and machine learning. He is a Senior Member of IEEE.
Preface 6
Acknowledgements 7
Contents 8
Abbreviations 10
List of Figures 12
List of Tables 14
1 Introduction 15
1.1 Channel Aggregation and Related Concepts 15
1.2 Channel Fragmentation Together with Channel Aggregation 17
1.3 Channel Access Schemes with Channel Aggregation and Fragmentation 17
1.3.1 Communication Standards Applying CA and CF 17
1.3.2 MAC Protocols in Research Articles EmployingCA and CF 18
1.4 Mathematical Analyses for CA and CF in CRNs 20
1.4.1 Resource Allocation in CRNs with CA and CF 21
1.4.2 MC Analysis for CRNs with CA and CF 22
1.5 The Main Goal and the Organization of the Book 25
References 26
2 Markov Chain and Stationary Distribution 30
2.1 Basic Concept of MC 30
2.2 Introduction to DTMC 31
2.3 Introduction to CTMC 34
References 41
3 Markov Chain Analysis of CA and CF with a Single Type of Users 42
3.1 Flow Types and System Configurations 42
3.1.1 Real-Time and Elastic Traffic Flows 42
3.1.2 System Configuration and Basic Assumptions 43
3.2 Analytical Models Based on CTMC 44
3.2.1 System Model without CA and CF 44
3.2.2 System Model with CA and CF 45
3.2.2.1 Models for Elastic Flows 45
3.2.2.2 Models for Real-Time Flows 52
3.2.3 Numerical Results 53
3.2.4 Capacity Upper Bound of Elastic Traffic Flows 58
3.2.4.1 Capacity Upper Bound of EFAFS(W,V) 59
3.2.4.2 Capacity Upper Bound in General 62
3.2.5 The Equivalence of EFAFS(W,V) and Dy(W,V) 65
3.2.6 System with a Finite Number of Users 68
3.3 Discussions and Summary 69
References 69
4 Markov Chain Analysis of CA and CF with Multiple Types of Users 71
4.1 Analytical Models Based on CTMCs for CRNs 71
4.1.1 System Configurations and Access Strategies 71
4.1.2 The Precise Model for EFAFS with Elastic Flows 73
4.1.3 The Model of EFAFS in the QSR for Elastic Flows 76
4.1.4 Capacity Upper Bound in the QSR for Elastic Flows 78
4.1.5 Models for Real-Time Flows 80
4.1.6 Numerical Results 82
4.2 Simulations and System Performance with Various Measurement-Based Distributions 88
4.2.1 Simulation Procedure 88
4.2.2 System Performance with Various Measurement-Based Distributions 92
4.3 Discussions and Summary 93
References 94
5 Test-Bed Evaluation of CA and CF via a Software Defined Radio 95
5.1 The Communication Scenario and the Access Strategies 95
5.2 System Design 96
5.2.1 Test-Bed Setup 96
5.2.2 Performance Metrics 99
5.3 Measurement Results 101
5.3.1 Numerical Configurations of the Test-Bed 101
5.3.2 Numerical Results 101
5.4 Discussions and Summary 103
References 103
Erscheint lt. Verlag | 25.11.2019 |
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Reihe/Serie | SpringerBriefs in Electrical and Computer Engineering | SpringerBriefs in Electrical and Computer Engineering |
Zusatzinfo | XV, 92 p. 102 illus., 37 illus. in color. |
Sprache | englisch |
Themenwelt | Technik ► Elektrotechnik / Energietechnik |
Technik ► Nachrichtentechnik | |
Schlagworte | Channel aggregation • Channel fragmentation • Cognitive Radio Network • Continuous time Markov chain • Discrete time Markov chain • Elastic flows • Markov process • performance evaluations • Real-time flows • Software Defined Radio • Stochastic process • Test-bed implementation • Traffic flows |
ISBN-10 | 3-030-33080-X / 303033080X |
ISBN-13 | 978-3-030-33080-4 / 9783030330804 |
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