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Cognitive Communication and Cooperative HetNet Coexistence : Selected Advances on Spectrum Sensing, Learning, and Security Approaches

By: Benedetto, Maria-Gabriella Di.
Contributor(s): Bader, Faouzi.
Material type: TextTextSeries: eBooks on Demand.Signals and Communication Technology: Publisher: Dordrecht : Springer, 2014Description: 1 online resource (372 p.).ISBN: 9783319014029.Subject(s): Artificial intelligence -- Congresses | Information technology -- Congresses | Software engineering -- CongressesGenre/Form: Electronic books.Additional physical formats: Print version:: Cognitive Communication and Cooperative HetNet Coexistence : Selected Advances on Spectrum Sensing, Learning, and Security ApproachesDDC classification: 004 | 621.384 LOC classification: T58.5TK5102.9Online resources: Click here to view this ebook.
Contents:
Preface; Acknowledgments; Contents; 1 Recent Advances on Wideband Spectrum Sensing for Cognitive Radio; 1.1 Introduction; 1.1.1 Sensing in the TV White Spaces; 1.2 Overview of Spectrum Sensing Algorithms; 1.2.1 Fundamental Detectors; 1.2.2 Diversity Based Sensing; 1.2.3 Cooperative Sensing; 1.3 Wideband Spectrum Sensing: A Review; 1.4 Wideband Sensing by Model Order Selection; 1.4.1 Information Theoretic Criteria (ITC); 1.4.2 DFT Based Wideband Algorithms; 1.5 Cooperative Wideband Spectrum Sensing; 1.6 Numerical Results and Discussion; 1.6.1 Independent Frequency Bins
1.6.2 Correlated Frequency Bins1.6.3 Multiband Sensing; 1.6.4 Cooperative Wideband Sensing; 1.7 Conclusions; References; 2 Channel Usage Patterns and Their Impact on the Effectiveness of Machine Learning for Dynamic Channel Selection; 2.1 Introduction; 2.2 Existing Works; 2.3 Complexity of Primary User Activity; 2.4 Learning and DCS; 2.4.1 Reinforcement Learning; 2.4.2 Markov-Based learning; 2.5 Results; 2.5.1 Reinforcement Learning; 2.5.2 Markov-Based Learning; 2.6 Conclusions; References; 3 Analysis and Optimization of Energy Detection for Non-Flat Spectral Characteristics
3.1 Introduction3.2 Basic Energy Detection Schemes; 3.2.1 Analytical Model; 3.2.2 FFT and Filter Bank Based Flexible Schemes for Multiband Sensing; 3.3 Energy Detection in the Presence of Frequency Variability; 3.3.1 Analytical Modeling; 3.3.2 Effects of the Frequency Response of Sensing Receiver; 3.3.3 Effects of Non-Flat Primary User Spectrum; 3.3.4 Effects of Fading Frequency Selective Channel; 3.4 Concluding Remarks; References; 4 Spectrum Sensing Algorithms for Cognitive TV White-Spaces Systems; 4.1 Introduction; 4.2 Single Antenna Spectrum Sensing Algorithms
4.2.1 Cyclic Prefix Based Detector4.2.2 Pilot-Based Detector; 4.3 Multi-Antenna Spectrum Sensing Algorithms; 4.3.1 System Model; 4.3.2 Algorithms with known noise variance; 4.3.3 Algorithms with unknown noise variance; 4.4 Channel Models; 4.4.1 Additive White Gaussian Noise Channel Model; 4.4.2 Flat Rayleigh Fading Channel Model; 4.4.3 Typical Urban 6-Path Channel Model; 4.5 Performance Assessment and Trade-Offs; 4.5.1 Results; 4.6 Conclusions; References; 5 New Blind Free-Band Detectors Exploiting Cyclic Autocorrelation Function Sparsity; 5.1 Introduction
5.2 A New Cyclic Autocorrelation Estimator Using Compressed Sensing5.2.1 CAF and Sparsity; 5.2.2 Classic Estimation of the Cyclic Autocorrelation Vector; 5.2.3 Blind Estimation of the Cyclic Autocorrelation Vector Using Compressed Sensing; 5.2.4 Performance Analyses of the New Blind Estimator; 5.2.5 Analyzing the Error in the Estimation of the Position of the Cyclic Frequency: The MSEαf; 5.3 Reduced Complexity Blind Detection Using Sparsity; 5.3.1 Slot Comparison Methods (Hard and Soft); 5.3.2 The Symmetry Method; 5.4 Conclusion; References
6 Intersystem Coexistence and Cooperation Through Control Channels
Summary: This book, written by experts from universities and major industrial research laboratories, is devoted to the very hot topic of cognitive radio and networking for cooperative coexistence of heterogeneous wireless networks. Selected highly relevant advanced research is presented on spectrum sensing and progress toward the realization of accurate radio environment mapping, biomimetic learning for self-organizing networks, security threats (with a special focus on primary user emulation attack), and cognition as a tool for green next-generation networks.
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Electronic Book UT Tyler Online
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T58.5 | TK5102.9 (Browse shelf) http://uttyler.eblib.com/patron/FullRecord.aspx?p=1636467 Available EBL1636467

Preface; Acknowledgments; Contents; 1 Recent Advances on Wideband Spectrum Sensing for Cognitive Radio; 1.1 Introduction; 1.1.1 Sensing in the TV White Spaces; 1.2 Overview of Spectrum Sensing Algorithms; 1.2.1 Fundamental Detectors; 1.2.2 Diversity Based Sensing; 1.2.3 Cooperative Sensing; 1.3 Wideband Spectrum Sensing: A Review; 1.4 Wideband Sensing by Model Order Selection; 1.4.1 Information Theoretic Criteria (ITC); 1.4.2 DFT Based Wideband Algorithms; 1.5 Cooperative Wideband Spectrum Sensing; 1.6 Numerical Results and Discussion; 1.6.1 Independent Frequency Bins

1.6.2 Correlated Frequency Bins1.6.3 Multiband Sensing; 1.6.4 Cooperative Wideband Sensing; 1.7 Conclusions; References; 2 Channel Usage Patterns and Their Impact on the Effectiveness of Machine Learning for Dynamic Channel Selection; 2.1 Introduction; 2.2 Existing Works; 2.3 Complexity of Primary User Activity; 2.4 Learning and DCS; 2.4.1 Reinforcement Learning; 2.4.2 Markov-Based learning; 2.5 Results; 2.5.1 Reinforcement Learning; 2.5.2 Markov-Based Learning; 2.6 Conclusions; References; 3 Analysis and Optimization of Energy Detection for Non-Flat Spectral Characteristics

3.1 Introduction3.2 Basic Energy Detection Schemes; 3.2.1 Analytical Model; 3.2.2 FFT and Filter Bank Based Flexible Schemes for Multiband Sensing; 3.3 Energy Detection in the Presence of Frequency Variability; 3.3.1 Analytical Modeling; 3.3.2 Effects of the Frequency Response of Sensing Receiver; 3.3.3 Effects of Non-Flat Primary User Spectrum; 3.3.4 Effects of Fading Frequency Selective Channel; 3.4 Concluding Remarks; References; 4 Spectrum Sensing Algorithms for Cognitive TV White-Spaces Systems; 4.1 Introduction; 4.2 Single Antenna Spectrum Sensing Algorithms

4.2.1 Cyclic Prefix Based Detector4.2.2 Pilot-Based Detector; 4.3 Multi-Antenna Spectrum Sensing Algorithms; 4.3.1 System Model; 4.3.2 Algorithms with known noise variance; 4.3.3 Algorithms with unknown noise variance; 4.4 Channel Models; 4.4.1 Additive White Gaussian Noise Channel Model; 4.4.2 Flat Rayleigh Fading Channel Model; 4.4.3 Typical Urban 6-Path Channel Model; 4.5 Performance Assessment and Trade-Offs; 4.5.1 Results; 4.6 Conclusions; References; 5 New Blind Free-Band Detectors Exploiting Cyclic Autocorrelation Function Sparsity; 5.1 Introduction

5.2 A New Cyclic Autocorrelation Estimator Using Compressed Sensing5.2.1 CAF and Sparsity; 5.2.2 Classic Estimation of the Cyclic Autocorrelation Vector; 5.2.3 Blind Estimation of the Cyclic Autocorrelation Vector Using Compressed Sensing; 5.2.4 Performance Analyses of the New Blind Estimator; 5.2.5 Analyzing the Error in the Estimation of the Position of the Cyclic Frequency: The MSEαf; 5.3 Reduced Complexity Blind Detection Using Sparsity; 5.3.1 Slot Comparison Methods (Hard and Soft); 5.3.2 The Symmetry Method; 5.4 Conclusion; References

6 Intersystem Coexistence and Cooperation Through Control Channels

This book, written by experts from universities and major industrial research laboratories, is devoted to the very hot topic of cognitive radio and networking for cooperative coexistence of heterogeneous wireless networks. Selected highly relevant advanced research is presented on spectrum sensing and progress toward the realization of accurate radio environment mapping, biomimetic learning for self-organizing networks, security threats (with a special focus on primary user emulation attack), and cognition as a tool for green next-generation networks.

Description based upon print version of record.

Author notes provided by Syndetics

<p>Maria-Gabriella Di Benedetto is Full Professor of Telecommunications at Sapienza University of Rome, Italy. Since 2000, she has been active in fostering the development of ultra-wide-band (UWB) radio communications in Europe and has participated in several pioneering EU projects on UWB communications. Her main research focus in the past decade has been on medium access control and management in wireless networks, as well as energy-efficient routing and location-based optimization of medium access control and routing functions.</p> <p>Faouzi Bader is Senior Research Associate at the École Supérieure d'Électricité (SUPELEC) in Rennes, France. His research activities mainly focus on advanced multicarrier waveforms for future communication systems, professional mobile radio/public protection and disaster relief and beyond, cross-layer system design, cognitive radio resource management and spectrum sharing, and system coexistence.</p>

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