Rawat / Song / Shetty Dynamic Spectrum Access for Wireless Networks

1. Auflage 2015
ISBN: 978-3-319-15299-8
Verlag: Springer Nature Switzerland
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 83 Seiten

Reihe: SpringerBriefs in Electrical and Computer Engineering

This SpringerBrief presents adaptive resource allocation schemes for secondary users for dynamic spectrum access (DSA) in cognitive radio networks (CRNs) by considering Quality-of-Service requirements, admission control, power/rate control, interference constraints, and the impact of spectrum sensing or primary user interruptions. It presents the challenges, motivations, and applications of the different schemes. The authors discuss cloud-assisted geolocation-aware adaptive resource allocation in CRNs by outsourcing computationally intensive processing to the cloud. Game theoretic approaches are presented to solve resource allocation problems in CRNs. Numerical results are presented to evaluate the performance of the proposed methods. Adaptive Resource Allocation in Cognitive Radio Networks is designed for professionals and researchers working in the area of wireless networks. Advanced-level students in electrical engineering and computer science, especially those focused on wireless networks, will find this information helpful.

Autoren/Hrsg.

Rawat, Danda B.

Song, Min

Shetty, Sachin

Inhaltsverzeichnis

1;Preface;8
2;Acknowledgments;10
3;Contents;12
4;List of Figures;14
5;List of Tables;16
6;1 An Overview of Cognitive Radio Networks;17
6.1;1.1 Introduction;17
6.2;1.2 Cognitive Radio Networks;18
6.3;1.3 System Model for Cognitive Radio Networks;19
6.4;1.4 Spectrum Sensing in Cognitive Radio Networks;20
6.4.1;1.4.1 Primary Transmitter Detection;20
6.4.2;1.4.2 Primary Receiver Detection;23
6.4.3;1.4.3 Cooperative Detection;23
6.4.4;1.4.4 Interference Temperature Management;24
6.5;1.5 Adaptation and Act/Communication Phases;24
6.6;1.6 Challenges and Motivations;25
6.7;1.7 Organizations and Summary;25
6.8;References;26
7;2 Resource Allocation in Spectrum Underlay Cognitive Radio Networks;28
7.1;2.1 Overview;28
7.2;2.2 Network Model and Problem Formulation;29
7.2.1;2.2.1 Distributed Admission Control for SUs;31
7.2.2;2.2.2 Power Control;31
7.2.3;2.2.3 Problem Formulation;32
7.3;2.3 Game Formulation;33
7.4;2.4 The Algorithm;34
7.5;2.5 Numerical Results;35
7.6;2.6 Waiting Probability for DSA in TDMA CRNs;36
7.6.1;2.6.1 Numerical Results;38
7.7;2.7 Summary;38
7.8;References;39
8;3 Resource Allocation in Spectrum Overlay Cognitive Radio Networks;40
8.1;3.1 Introduction;40
8.2;3.2 Network Model and Problem Formulation;41
8.3;3.3 Two-Stage Stackelberg Game;44
8.3.1;3.3.1 Follower Rate Maximization Sub-Game (FRMG);44
8.3.2;3.3.2 The Leader Price Selection Sub-Game (LPSG);47
8.3.3;3.3.3 The Best Response for the Stackelberg Game;49
8.3.4;3.3.4 The Existence and Uniqueness of the Equilibrium;50
8.4;3.4 The Algorithm;51
8.5;3.5 Numerical Results;51
8.6;3.6 Summary;55
8.7;References;55
9;4 Cloud-Integrated Geolocation-Aware Dynamic Spectrum Access;58
9.1;4.1 Introduction;58
9.2;4.2 System Model;59
9.3;4.3 Computing Platform;60
9.3.1;4.3.1 Distributed Computation;61
9.3.2;4.3.2 Distributed Database;61
9.4;4.4 Infrastructure-Based SU Communications;62
9.4.1;4.4.1 Numerical Results;63
9.5;4.5 Distributed Power Adaptation Game (DPAG) for Peer-to-Peer SU Communications;66
9.5.1;4.5.1 Numerical Results;69
9.6;4.6 Summary;70
9.7;References;70
10;5 Resource Allocation for Cognitive Radio Enabled Vehicular Network Users;72
10.1;5.1 Introduction;72
10.2;5.2 Networks Model;73
10.3;5.3 Analysis for Connectivity in VANET;74
10.4;5.4 Numerical Results;76
10.5;5.5 Summary;79
10.6;References;79
11;Author Biographies;81
12;Index;83