1 An Overview of Cognitive Radio Networks . . . . . . . . . . 1
1.1 Introduction . . . . . . . . . . . . . . . . . . . 1
1.2 Cognitive Radio Networks. . . . . . . . . . . . . . . . . . . . . . . 2
1.3 System Model for Cognitive Radio Networks . . . . . . . . 3
1.4 Spectrum Sensing in Cognitive Radio Networks . . . . . . . 4
1.4.1 Primary Transmitter Detection . . . . . . . . . . . 4
1.4.2 Primary Receiver Detection . . . . . . . . . . . . . 7
1.4.3 Cooperative Detection . . . . . . . . . . . . . . . . . . . . . 7
1.4.4 Interference Temperature Management. . . . . . . . 8
1.5 Adaptation and Act/Communication Phases. . . . . . . . . . . 8
1.6 Challenges and Motivations . . . . . .. . . . . . . . . . . . . . . . 9
1.7 Organizations and Summary . . . . . . . . . . . . . . . . . . . 9
2 Resource Allocation in Spectrum Underlay Cognitive Radio Networks 13
2.1 Overview . . . . . . . . . . . . . . . . . . . . .. 13
2.2 Network Model and Problem Formulation . . . . . . . . . . .. 14
2.2.1 Distributed Admission Control for SUs . . . . . . 16
2.2.2 Power Control. . . . . . . . . .. . . . . . . . . . . . . . . 16
2.2.3 Problem Formulation . . . . . . . . . . . . . . . . . 17
2.3 Game Formulation . . . . . . . . . . . . . . . . . . . . . . . . . . 18
2.4 The Algorithm. . . . . . . . . . . . . . . . . . . . . . . . . . . 19
2.5 Numerical Results. . . . .. . . . . . . . . . . . . . . . . . . . . 20
2.6 Waiting Probability for DSA in TDMA CRNs . . 21
2.6.1 Numerical Results . . . . . . . . . . . . . . . . . . 23
3 Resource Allocation in Spectrum Overlay Cognitive Radio Networks . 25
3.1 Introduction . . . . . . . . . . . . . . . . . . .. 25
3.2 Network Model and Problem Formulation . . . . . . . . 26
3.3 Two-Stage Stackelberg Game . . . . . . . . . 29
3.3.1 Follower Rate Maximization Sub-Game (FRMG) . . . . . . 29
3.3.2 The Leader Price Selection Sub-Game (LPSG) . . . . . 32
3.3.3 The Best Response for the Stackelberg Game. . . . . . 34
3.3.4 The Existence and Uniqueness of the Equilibrium. . . . 35
3.4 The Algorithm. . . . . . . . . . . . . . . . . . . . . . . . 36
3.5 Numerical Results. . . . . . . . . . . . . . . . . . . . . . . . . 36
4 Cloud-Integrated Geolocation-Aware Dynamic Spectrum Access . . . . . . 43
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . 43
4.2 System Model . . . . . . . . . . . . . . . . . . . . . . . . 44
4.3 Computing Platform . . . . . . . . . . . . . . . . . . . . 45
4.3.1 Distributed Computation. . . . . . . . . . 46
4.3.2 Distributed Database. . . . . . . . . . 46
4.4 Infrastructure-Based SU Communications. . 47
4.4.1 Numerical Results . . . . . . . . . . . . . . . . . 48
4.5 Distributed Power Adaptation Game (DPAG)
for Peer-to-Peer SU Communications. . . . . . . 51
4.5.1 Numerical Results . . . . . . . . . . . . . . 54
5 Resource Allocation for Cognitive Radio Enabled Vehicular Network User 57
5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . 57
5.2 Networks Model . . . . . . . . . . . . . . . . . . . . . . . 58
5.3 Analysis for Connectivity in VANET . . . . . . . . 59
5.4 Numerical Results. . . .. . . . . . . . . . . . . . . . . 61
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