17,744 research outputs found

    Optimal Cooperative Spectrum Sensing for Cognitive Radio

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    The rapid increasing interest in wireless communication has led to the continuous development of wireless devices and technologies. The modern convergence and interoperability of wireless technologies has further increased the amount of services that can be provided, leading to the substantial demand for access to the radio frequency spectrum in an efficient manner. Cognitive radio (CR) an innovative concept of reusing licensed spectrum in an opportunistic manner promises to overcome the evident spectrum underutilization caused by the inflexible spectrum allocation. Spectrum sensing in an unswerving and proficient manner is essential to CR. Cooperation amongst spectrum sensing devices are vital when CR systems are experiencing deep shadowing and in a fading environment. In this thesis, cooperative spectrum sensing (CSS) schemes have been designed to optimize detection performance in an efficient and implementable manner taking into consideration: diversity performance, detection accuracy, low complexity, and reporting channel bandwidth reduction. The thesis first investigates state of the art spectrums sensing algorithms in CR. Comparative analysis and simulation results highlights the different pros, cons and performance criteria of a practical CSS scheme leading to the problem formulation of the thesis. Motivated by the problem of diversity performance in a CR network, the thesis then focuses on designing a novel relay based CSS architecture for CR. A major cooperative transmission protocol with low complexity and overhead - Amplify and Forward (AF) cooperative protocol and an improved double energy detection scheme in a single relay and multiple cognitive relay networks are designed. Simulation results demonstrated that the developed algorithm is capable of reducing the error of missed detection and improving detection probability of a primary user (PU). To improve spectrum sensing reliability while increasing agility, a CSS scheme based on evidence theory is next considered in this thesis. This focuses on a data fusion combination rule. The combination of conflicting evidences from secondary users (SUs) with the classical Dempster Shafter (DS) theory rule may produce counter-intuitive results when combining SUs sensing data leading to poor CSS performance. In order to overcome and minimise the effect of the counter-intuitive results, and to enhance performance of the CSS system, a novel state of the art evidence based decision fusion scheme is developed. The proposed approach is based on the credibility of evidence and a dissociability degree measure of the SUs sensing data evidence. Simulation results illustrate the proposed scheme improves detection performance and reduces error probability when compared to other related evidence based schemes under robust practcial scenarios. Finally, motivated by the need for a low complexity and minmum bandwidth reporting channels which can be significant in high data rate applications, novel CSS quantization schemes are proposed. Quantization methods are considered for a maximum likelihood estimation (MLE) and an evidence based CSS scheme. For the MLE based CSS, a novel uniform and optimal output entropy quantization scheme is proposed to provide fewer overhead complexities and improved throughput. While for the Evidence based CSS scheme, a scheme that quantizes the basic probability Assignment (BPA) data at each SU before being sent to the FC is designed. The proposed scheme takes into consideration the characteristics of the hypothesis distribution under diverse signal-to-noise ratio (SNR) of the PU signal based on the optimal output entropy. Simulation results demonstrate that the proposed quantization CSS scheme improves sensing performance with minimum number of quantized bits when compared to other related approaches

    Byzantine Attack and Defense in Cognitive Radio Networks: A Survey

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    The Byzantine attack in cooperative spectrum sensing (CSS), also known as the spectrum sensing data falsification (SSDF) attack in the literature, is one of the key adversaries to the success of cognitive radio networks (CRNs). In the past couple of years, the research on the Byzantine attack and defense strategies has gained worldwide increasing attention. In this paper, we provide a comprehensive survey and tutorial on the recent advances in the Byzantine attack and defense for CSS in CRNs. Specifically, we first briefly present the preliminaries of CSS for general readers, including signal detection techniques, hypothesis testing, and data fusion. Second, we analyze the spear and shield relation between Byzantine attack and defense from three aspects: the vulnerability of CSS to attack, the obstacles in CSS to defense, and the games between attack and defense. Then, we propose a taxonomy of the existing Byzantine attack behaviors and elaborate on the corresponding attack parameters, which determine where, who, how, and when to launch attacks. Next, from the perspectives of homogeneous or heterogeneous scenarios, we classify the existing defense algorithms, and provide an in-depth tutorial on the state-of-the-art Byzantine defense schemes, commonly known as robust or secure CSS in the literature. Furthermore, we highlight the unsolved research challenges and depict the future research directions.Comment: Accepted by IEEE Communications Surveys and Tutoiral

    Collaborative spectrum sensing optimisation algorithms for cognitive radio networks

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    The main challenge for a cognitive radio is to detect the existence of primary users reliably in order to minimise the interference to licensed communications. Hence, spectrum sensing is a most important requirement of a cognitive radio. However, due to the channel uncertainties, local observations are not reliable and collaboration among users is required. Selection of fusion rule at a common receiver has a direct impact on the overall spectrum sensing performance. In this paper, optimisation of collaborative spectrum sensing in terms of optimum decision fusion is studied for hard and soft decision combining. It is concluded that for optimum fusion, the fusion centre must incorporate signal-to-noise ratio values of cognitive users and the channel conditions. A genetic algorithm-based weighted optimisation strategy is presented for the case of soft decision combining. Numerical results show that the proposed optimised collaborative spectrum sensing schemes give better spectrum sensing performance

    Enforcement in Dynamic Spectrum Access Systems

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    The spectrum access rights granted by the Federal government to spectrum users come with the expectation of protection from harmful interference. As a consequence of the growth of wireless demand and services of all types, technical progress enabling smart agile radio networks, and on-going spectrum management reform, there is both a need and opportunity to use and share spectrum more intensively and dynamically. A key element of any framework for managing harmful interference is the mechanism for enforcement of those rights. Since the rights to use spectrum and to protection from harmful interference vary by band (licensed/unlicensed, legacy/newly reformed) and type of use/users (primary/secondary, overlay/underlay), it is reasonable to expect that the enforcement mechanisms may need to vary as well.\ud \ud In this paper, we present a taxonomy for evaluating alternative mechanisms for enforcing interference protection for spectrum usage rights, with special attention to the potential changes that may be expected from wider deployment of Dynamic Spectrum Access (DSA) systems. Our exploration of how the design of the enforcement regime interacts with and influences the incentives of radio operators under different rights regimes and market scenarios is intended to assist in refining thinking about appropriate access rights regimes and how best to incentivize investment and growth in more efficient and valuable uses of the radio frequency spectrum

    Spectrum sharing security and attacks in CRNs: a review

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    Cognitive Radio plays a major part in communication technology by resolving the shortage of the spectrum through usage of dynamic spectrum access and artificial intelligence characteristics. The element of spectrum sharing in cognitive radio is a fundament al approach in utilising free channels. Cooperatively communicating cognitive radio devices use the common control channel of the cognitive radio medium access control to achieve spectrum sharing. Thus, the common control channel and consequently spectrum sharing security are vital to ensuring security in the subsequent data communication among cognitive radio nodes. In addition to well known security problems in wireless networks, cognitive radio networks introduce new classes of security threats and challenges, such as licensed user emulation attacks in spectrum sensing and misbehaviours in the common control channel transactions, which degrade the overall network operation and performance. This review paper briefly presents the known threats and attacks in wireless networks before it looks into the concept of cognitive radio and its main functionality. The paper then mainly focuses on spectrum sharing security and its related challenges. Since spectrum sharing is enabled through usage of the common control channel, more attention is paid to the security of the common control channel by looking into its security threats as well as protection and detection mechanisms. Finally, the pros and cons as well as the comparisons of different CR - specific security mechanisms are presented with some open research issues and challenges

    A Study on Techniques/Algorithms used for Detection and Prevention of Security Attacks in Cognitive Radio Networks

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    In this paper a detailed survey is carried out on the taxonomy of Security Issues, Advances on Security Threats and Countermeasures ,A Cross-Layer Attack, Security Status and Challenges for Cognitive Radio Networks, also a detailed survey on several Algorithms/Techniques used to detect and prevent SSDF(Spectrum Sensing Data Falsification) attack a type of DOS (Denial of Service) attack and several other  Network layer attacks in Cognitive Radio Network or Cognitive Radio Wireless Sensor Node Networks(WSNN’s) to analyze the advantages and disadvantages of those existing algorithms/techniques

    Decoupling trust and wireless channel induced effects on collaborative sensing attacks

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    One of the most crucial functionalities of cognitive radio networks is spectrum sensing. Completing this task in an accurate manner requires opportunistic spectrum access. Traditionally, sensing has been performed through energy detection by each individual secondary user. In order to increase accuracy, individual measurements are aggregated using different fusion functions. However, even though collaborative spectrum sensing can increase accuracy under benign settings, it is prone to falsification attacks, where malicious secondary users report fake sensings. Previous studies have designed trust (reputation) based systems to contain the effect of the adversaries, ignoring to a large extent the wireless channel irregularities when performing the computation. In this paper, we decouple the reasons behind an incorrect sensing report and propose the Decoupling Trust and Capability Spectrum Sensing System (DTCS3). DTCS3 is a collaborative spectrum sensing system that takes into account both a secondary sensor node's trust and its capability to sense the channel. Through thorough evaluations that consider a large variety of attack strategies, we show that by accounting for wireless induced effects while calculating the reporting trust of a secondary user, we can significantly improve the performance of a collaborative spectrum sensing system as compared to existing schemes in the literature. In particular, the true positive/negative rates can be improved by as much as 38%, while DTCS 3 is able to track and respond to dynamic changes in the adversaries' behavior. © 2014 IEEE
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