Robust And Secure Spectrum Sensing In Cognitive Radio Networks

With wireless devices and applications booming, the problem of inefficient utilization of the precious radio spectrum has arisen. Cognitive radio is a key technology to improve spectrum utilization. A major challenge in cognitive radio networks is spectrum sensing, which detects if a spectrum band is being used by a primary user. Spectrum sensing plays a critical role in cognitive radio networks. However, spectrum sensing is vulnerable to security attacks from malicious users. In this dissertation, we propose a malicious user detection scheme, a density based SSDF detection scheme, a conjugate prior based SSDF detection scheme, and an anti-jamming algorithm to achieve robust and secure cooperative spectrum sensing in cognitive radio networks. Performance analysis and simulation results show that our proposed schemes can achieve very good performance in detecting malicious users, excluding abnormal sensing reports, and defending the jamming attack, thus improve spectrum sensing performance in cognitive radio networks.

This book provides an overview of the latest research and development of new technologies for cognitive radio, mobile communications, and wireless networks. The contributors discuss the research and requirement analysis and initial standardization work towards 5G cellular systems and the capacity problems it presents. They show how cognitive radio, with the capability to flexibly adapt its parameters, has been proposed as the enabling technology for unlicensed secondary users to dynamically access the licensed spectrum owned by legacy primary users on a negotiated or an opportunistic basis. They go on to show how cognitive radio is now perceived in a much broader paradigm that will contribute to solve the resource allocation problem that 5G requirements raise. The chapters represent hand-selected expanded papers from EAI sponsored and hosted conferences such as the 12th EAI International Conference on Mobile and Ubiquitous Systems, the 11th EAI International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness, the 10th International Conference on Cognitive Radio Oriented Wireless Networks, the 8th International Conference on Mobile Multimedia Communications, and the EAI International Conference on Software Defined Wireless Networks and Cognitive Technologies for IoT.

This SpringerBrief discusses the applications of spare representation in wireless communications, with a particular focus on the most recent developed compressive sensing (CS) enabled approaches. With the help of sparsity property, sub-Nyquist sampling can be achieved in wideband cognitive radio networks by adopting compressive sensing, which is illustrated in this brief, and it starts with a comprehensive overview of compressive sensing principles. Subsequently, the authors present a complete framework for data-driven compressive spectrum sensing in cognitive radio networks, which guarantees robustness, low-complexity, and security. Particularly, robust compressive spectrum sensing, low-complexity compressive spectrum sensing, and secure compressive sensing based malicious user detection are proposed to address the various issues in wideband cognitive radio networks. Correspondingly, the real-world signals and data collected by experiments carried out during TV white space pilot trial enables data-driven compressive spectrum sensing. The collected data are analysed and used to verify our designs and provide significant insights on the potential of applying compressive sensing to wideband spectrum sensing. This SpringerBrief provides readers a clear picture on how to exploit the compressive sensing to process wireless signals in wideband cognitive radio networks. Students, professors, researchers, scientists, practitioners, and engineers working in the fields of compressive sensing in wireless communications will find this SpringerBrief very useful as a short reference or study guide book. Industry managers, and government research agency employees also working in the fields of compressive sensing in wireless communications will find this SpringerBrief useful as well.

Cognitive radio refers to the technology that the devices can intelligently access unused frequency resources which are originally reserved for legacy services in order to increase the spectrum utilization. At the mean time, the legacy services should not be affected by the access of cognitive radio devices. The common problems in cognitive radio are how to find unused frequency resources (spectrum sensing) and how to access them (spectrum accessing). This dissertation focuses on the robust methods of spectrum sensing as well as spectrum accessing strategies with the statistics of channel availabilities. The first part of the thesis studies non-parametric robust hypothesis testing problem to eliminate the effect of the uncertainty and instability introduced by non-stationary noise, which is constantly observed in communication systems. An empirical likelihood ratio test with density function constraints is proposed. This test outperforms many popular goodness-of-fit tests, including the robust Kolmogorov-Smirnov test and the Cramér-von Mises test, etc. Examples using spectrum sensing data with real-world noise samples are provided to show their performance. The second part focuses on channel idle time distribution based spectrum accessing strategies. Through the study of the real-world wireless local area network traffic, it is identified that the channel idle time distribution can be modeled using hyper-exponential distribution. With this model, the performance of a single cognitive radio, or the secondary user, is studied when the licensed user, or the primary user, does not react to interference. It is also shown that with the complete information of the hyper-exponential distribution, the secondary user can achieve a desirable performance. But when the model exhibits uncertainty and time non-stationarity, which would happen for any kind of wireless traffic, the secondary user suffers from huge performance loss. A strategy that is robust to the uncertainty is proposed. The performance of this strategy is demonstrated using experimental data. Another aspect of the problem is when the PU is reactive. In this case, a spectrum accessing strategy is devised to avoid large-duration interference to the PU. Additionally, the spectrum accessing strategies are also extended to the cognitive radio networks with multiple secondary users. A decentralized MAC protocol is devised which reaches a total secondary capacity performance close to the optimal. A discussion of the engineering aspects with practical consideration of spectrum sensing and accessing is given at the end.

Cognitive Radio Communications and Networks gives comprehensive and balanced coverage of the principles of cognitive radio communications, cognitive networks, and details of their implementation, including the latest developments in the standards and spectrum policy. Case studies, end-of-chapter questions, and descriptions of various platforms and test beds, together with sample code, give hands-on knowledge of how cognitive radio systems can be implemented in practice. Extensive treatment is given to several standards, including IEEE 802.22 for TV White Spaces and IEEE SCC41 Written by leading people in the field, both at universities and major industrial research laboratories, this tutorial text gives communications engineers, R&D engineers, researchers, undergraduate and post graduate students a complete reference on the application of wireless communications and network theory for the design and implementation of cognitive radio systems and networks Each chapter is written by internationally renowned experts, giving complete and balanced treatment of the fundamentals of both cognitive radio communications and cognitive networks, together with implementation details Extensive treatment of the latest standards and spectrum policy developments enables the development of compliant cognitive systems Strong practical orientation – through case studies and descriptions of cognitive radio platforms and testbeds – shows how real world cognitive radio systems and network architectures have been built Alexander M. Wyglinski is an Assistant Professor of Electrical and Computer Engineering at Worcester Polytechnic Institute (WPI), Director of the WPI Limerick Project Center, and Director of the Wireless Innovation Laboratory (WI Lab) Each chapter is written by internationally renowned experts, giving complete and balanced treatment of the fundamentals of both cognitive radio communications and cognitive networks, together with implementation details Extensive treatment of the latest standards and spectrum policy developments enables the development of compliant cognitive systems Strong practical orientation – through case studies and descriptions of cognitive radio platforms and testbeds – shows how "real world" cognitive radio systems and network architectures have been built

Fueled by ongoing and increasing consumer demand, the explosive growth in spectrum-based communications continues to tax the finite resources of the available spectrum. One possible solution, Cognitive Radio Network (CRN), allows unlicensed users opportunistic access to licensed bands without interfering with existing users. Although some initial s

This book constitutes the thoroughly refereed post-conference proceedings of the 7th International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness, QShine 2010. The 37 revised full papers presented along with 7 papers from the allocated Dedicated Short Range Communications Workshop, DSRC 2010, were carefully selected from numerous submissions. Conference papers are organized into 9 technical sessions, covering the topics of cognitive radio networks, security, resource allocation, wireless protocols and algorithms, advanced networking systems, sensor networks, scheduling and optimization, routing protocols, multimedia and stream processing. Workshop papers are organized into two sessions: DSRC networks and DSRC security.