5,724 research outputs found
Byzantine Attack and Defense in Cognitive Radio Networks: A Survey
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
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
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
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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