5,724 research outputs found

    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

    Power Allocation for Adaptive OFDM Index Modulation in Cooperative Networks

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    In this paper, we propose a power allocation strategy for the adaptive orthogonal frequency-division multiplexing (OFDM) index modulation (IM) in cooperative networks. The allocation strategy is based on the Karush-Kuhn-Tucker (KKT) conditions, and aims at maximizing the average network capacity according to the instantaneous channel state information (CSI). As the transmit power at source and relay is constrained separately, we can thus formulate an optimization problem by allocating power to active subcarriers. Compared to the conventional uniform power allocation strategy, the proposed dynamic strategy can lead to a higher average network capacity, especially in the low signal-to-noise ratio (SNR) region. The analysis is also verified by numerical results produced by Monte Carlo simulations. By applying the proposed power allocation strategy, the efficiency of adaptive OFDM IM can be enhanced in practice, which paves the way for its implementation in the future, especially for cell-edge communications

    Large-Scale Distributed Internet-based Discovery Mechanism for Dynamic Spectrum Allocation

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    Scarcity of frequencies and the demand for more bandwidth is likely to increase the need for devices that utilize the available frequencies more efficiently. Radios must be able to dynamically find other users of the frequency bands and adapt so that they are not interfered, even if they use different radio protocols. As transmitters far away may cause as much interference as a transmitter located nearby, this mechanism can not be based on location alone. Central databases can be used for this purpose, but require expensive infrastructure and planning to scale. In this paper, we propose a decentralized protocol and architecture for discovering radio devices over the Internet. The protocol has low resource requirements, making it suitable for implementation on limited platforms. We evaluate the protocol through simulation in network topologies with up to 2.3 million nodes, including topologies generated from population patterns in Norway. The protocol has also been implemented as proof-of-concept in real Wi-Fi routers.Comment: Accepted for publication at IEEE DySPAN 201

    Access Policy Design for Cognitive Secondary Users under a Primary Type-I HARQ Process

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    In this paper, an underlay cognitive radio network that consists of an arbitrary number of secondary users (SU) is considered, in which the primary user (PU) employs Type-I Hybrid Automatic Repeat Request (HARQ). Exploiting the redundancy in PU retransmissions, each SU receiver applies forward interference cancelation to remove a successfully decoded PU message in the subsequent PU retransmissions. The knowledge of the PU message state at the SU receivers and the ACK/NACK message from the PU receiver are sent back to the transmitters. With this approach and using a Constrained Markov Decision Process (CMDP) model and Constrained Multi-agent MDP (CMMDP), centralized and decentralized optimum access policies for SUs are proposed to maximize their average sum throughput under a PU throughput constraint. In the decentralized case, the channel access decision of each SU is unknown to the other SU. Numerical results demonstrate the benefits of the proposed policies in terms of sum throughput of SUs. The results also reveal that the centralized access policy design outperforms the decentralized design especially when the PU can tolerate a low average long term throughput. Finally, the difficulties in decentralized access policy design with partial state information are discussed
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