Cognitive Radio Networks Optimization with Spectrum Sensing Algorithms / anuja S. Dhope.

Format:

Book

Author/Creator:

Dhope, Tanuja Shendkar, author.

Series:

River Publishers series in communications ; Volume 44.

River Publishers Series in Communications ; Volume 44

Language:

English

Subjects (All):

Cognitive radio networks.

Physical Description:

1 online resource (191 pages) : illustrations (some color), tables, graphs.

Edition:

1st ed.

Place of Publication:

Gistrup, Denmark : River Publishers, [2015]

Summary:

This book focuses on Television White Space (TVWS) opportunities and regulatory aspects for cognitive radio applications, and includes case studies for the exploitation of TVWS depending on user's mobility, and the geo-location between user and the Base Station.

Contents:

Cover

Half Title - Cognitive Radio Networks Optimization with Spectrum Sensing Algorithms

Seres in River Publishers

Title - Cognitive Radio Networks Optimization with Spectrum Sensing Algorithms

Copyright

Contents

Preface

Acknowledgments

List of Figures

List of Tables

List of Abbreviations

Chapter_1 Novel Application of TV White Space

1.1 Introduction

1.2 DD: International Scenario

1.3 Regulatory Framework in India

1.4 DD: Indian Scenario

1.4.1 Spectrum Allocation in India

1.5 Joint Task Group and 700 MHz

1.6 Opportunistic Spectrum Access in India

1.7 Opportunities inTVWS

1.7.1 Wide Area Coverage in Rural Areas (e.g. IEEE 802.22)

1.7.2 Super Wi-Fi/Low-Power Broadband (e.g. IEEE 802.11af)

1.7.3 Broadcasting Services

1.7.4 DVB-H with Cognitive Access toTVWS

1.7.5 LTE Extension

1.7.6 Femto Cell for Wireless Broadband inTVWS

1.7.7 Public Safety Application

1.8 Empowering Rural India

1.8.1 E-Agriculture

1.8.2 E-Animal Husbandry

1.8.3 E-Health

1.8.4 E-Education

1.8.5 E-Governance

1.9 Use Cases forTVWS Usage

1.9.1 Use Case: Mid-/Long-Range Wireless Access

1.9.1.1 Mid-/long-range: no mobility

1.9.1.2 Mid-/long-range: low mobility

1.9.1.3 Mid-/long range: high mobility

1.9.1.4 Centralized network management

1.9.2 Use Case: Short-Range Wireless Access

1.9.2.1 Uncoordinated networks

1.9.2.2 Coordinated networks

1.9.2.3 Hybrid of uncoordinated and coordinated networks

1.9.3 Use Case: Opportunistic Spectrum Access by CellularSystems

1.9.4 Use Case: Ad Hoc Networking overWS Frequency Bands

1.11 Regulatory Activities Related to CR andTVWS

1.12 Conclusions

1.10 QoS inTVWS

1.10.1 High QoS

1.10.2 Moderate QoS

References

Chapter_2 Spectrum Sensing in Cognitive Radio

2.1 Introduction.

2.2 Dynamic Spectrum Access

2.3 Cognitive Radio

2.4 Spectrum Sensing Challenges

2.4.1 Hidden Primary User Problem

2.4.2 Channel Uncertainty

2.4.3 Noise Uncertainty

2.4.4 Cross-Layer Design

2.4.5 Spread Spectrum Primary Users Detection

2.4.6 Sensing Duration and Frequency

2.4.7 Decision Fusion in Cooperative Sensing

2.4.8 Security and Trusted Access

2.4.9 Spectrum Sensing in Multidimensional Environment

2.4.10 Interference Temperature Measurement

2.4.11 Complexity Issue

2.5 Characteristics of Spectrum Sensing

2.6 Spectrum Sensing Methods

2.6.1 Matched Filtering

2.6.2 Cyclostationary Detection

2.6.3 GLRT

2.6.4 Multitaper Spectrum Estimation

2.6.5 Wavelets

2.6.6 Energy Detection

2.6.7 Covariance-based Method

2.6.8 Other Spectrum Sensing Methods

2.7 Analysis of Energy Detection and CovarianceAbsolute Value Method

2.7.1 Energy Detection

2.7.2 Covariance Absolute Value

2.7.2.1 Steps for obtaining the pre-whiten matrix

2.7.2.2 Flow Chart for CAV method

2.7.3 Simulation Results for ED without Noise Uncertaintyand CAV

2.7.4 Simulation Results for ED with Noise Uncertainty and CAV

2.8 Hybrid Detection Method

2.8.1 Comparison between ED- and CAV-based Detection

Computational complexity

2.8.2 Hybrid Detection Method

2.8.2.1 Analysis of Hybrid Detection Method

2.8.2.2 Probability distribution function of βHD

2.8.2.3 Threshold calculation for hybrid detection method

2.8.2.4 Computational Complexity

2.8.3 Simulation Results for Hybrid Detection Method

2.8.4 Simulation Results for Hybrid Detection Methodover Fading Channels

2.9 Conclusions

Chapter _ 3 Cooperative Spectrum Sensing

3.1 Introduction

3.2 Need for Cooperative Sensing

3.3 Classification of Cooperative Sensing

3.3.1 Centralized Cooperative Sensing.

3.3.2 Distributed Cooperative Sensing

3.3.3 Relay-Assisted Cooperative Sensing

3.4 Cooperative Sensing based on Data Fusion

3.4.1 Soft Combining

3.4.2 Quantized Soft Combining

3.4.3 Hard Combining

3.4.3.1 Logical-OR rule

3.4.3.2 Logical-AND rule

3.4.3.3 "K out of Q" rule

3.5 Cooperative Spectrum Sensing System Model

3.6 Characterization of the Radio Path Environment

3.6.1 Outdoor Modeling, AWGN Channel

3.6.2 Indoor Modeling, Rayleigh Fading

3.7 Simulation Results

3.8 Conclusions

Chapter _ 4 DoA Estimation Algorithms

4.1 Introduction

4.2 Smart Antenna System and SDMA

4.3 Classification of DoA

4.3.1 System Model

4.3.2 Beamforming Techniques

4.3.2.1 Bartlett's method

4.3.2.2 Capon's method

4.3.3 Subspace-based Methods

4.3.3.1 Music algorithm

4.3.3.2 Esprit algorithm

4.3.3.3 root-Music algorithm

4.4 Simulation Results for MUSIC, root-Music and ESPRIT

4.4.1 Impact of Array Elements on MUSIC Spectrum

4.4.2 Impact of SNR on MUSIC Spectrum

4.4.3 Impact of Snapshots on MUSIC Spectrum

4.4.4 Impact of Snapshots (M = 8, SNR = 10 dB, four signals: 140,280, 350, 550)

4.4.5 Impact of Number of Snapshots (SNR = 10 dB, arraysize = 16)

4.4.6 Impact of Number of Array Elements (SNR = 10 dB,snapshots = 200)

4.4.7 Impact of SNR

4.5 Simulation Results for Music, CAPON and root-MUSIC

4.5.1 Impact of Number of Array Elements

4.5.2 Impact of Number of Snapshots

4.5.3 Impact of SNR

4.5.4 Performance with DoAs around 90◦

4.6 DoA/AoA Estimation Algorithm in Cognitive RadioContext

4.7 Simulation Results for Capon, Bartlett's, MUSIC,ESPRIT and root-MUSIC

4.7.1 Impact of Array Elements

4.7.2 Impact of Snapshots

4.7.3 Impact of SNR

4.7.4 Time-Varying Fading Rayleigh Channel

4.7.5 Proposal of a Better Performing Algorithm.

4.8 Conclusions

Index

Author Biography.

Notes:

Includes bibliographical references and index.

Description based on print version record.

ISBN:

1-00-333760-0

1-000-79606-X

1-003-33760-0

87-93102-01-1

9781003337607

OCLC:

957124684