658 research outputs found
Novel SαS PDF approximations and their applications in wireless signal detection
Three new approximations to the probability density function (PDF) of the symmetric alpha stable (SαS) distribution are proposed. The first two approximations use rational functions while the third approximation uses power functions. Using these approximations, new detectors for signals in symmetric alpha stable noise are also derived. Numerical results show that all these new approximations have good accuracies. Numerical results also show that the new detectors based on these approximations outperform the existing detectors, especially when the characteristic exponent of the symmetric alpha stable distribution is small
A Scalable Hybrid MAC Protocol for Massive M2M Networks
In Machine to Machine (M2M) networks, a robust Medium Access Control (MAC)
protocol is crucial to enable numerous machine-type devices to concurrently
access the channel. Most literatures focus on developing simplex (reservation
or contention based)MAC protocols which cannot provide a scalable solution for
M2M networks with large number of devices. In this paper, a frame-based Hybrid
MAC scheme, which consists of a contention period and a transmission period, is
proposed for M2M networks. In the proposed scheme, the devices firstly contend
the transmission opportunities during the contention period, only the
successful devices will be assigned a time slot for transmission during the
transmission period. To balance the tradeoff between the contention and
transmission period in each frame, an optimization problem is formulated to
maximize the system throughput by finding the optimal contending probability
during contention period and optimal number of devices that can transmit during
transmission period. A practical hybrid MAC protocol is designed to implement
the proposed scheme. The analytical and simulation results demonstrate the
effectiveness of the proposed Hybrid MAC protocol
Game among Interdependent Networks: The Impact of Rationality on System Robustness
Many real-world systems are composed of interdependent networks that rely on
one another. Such networks are typically designed and operated by different
entities, who aim at maximizing their own payoffs. There exists a game among
these entities when designing their own networks. In this paper, we study the
game investigating how the rational behaviors of entities impact the system
robustness. We first introduce a mathematical model to quantify the interacting
payoffs among varying entities. Then we study the Nash equilibrium of the game
and compare it with the optimal social welfare. We reveal that the cooperation
among different entities can be reached to maximize the social welfare in
continuous game only when the average degree of each network is constant.
Therefore, the huge gap between Nash equilibrium and optimal social welfare
generally exists. The rationality of entities makes the system inherently
deficient and even renders it extremely vulnerable in some cases. We analyze
our model for two concrete systems with continuous strategy space and discrete
strategy space, respectively. Furthermore, we uncover some factors (such as
weakening coupled strength of interdependent networks, designing suitable
topology dependency of the system) that help reduce the gap and the system
vulnerability
Full Wave Modeling of Ultrasonic Scattering Using Nystrom Method for NDE Applications
Approximate methods for ultrasonic scattering like the Kirchhoff approximation and the geometrical theory of diffraction (GTD) can deliver fast solutions with relatively small computational resources compared to accurate numerical methods. However, these models are prone to inaccuracies in predicting scattered fields from defects that are not very large compared to wavelength. Furthermore, they do not take into account physical phenomena like multiple scattering and surface wave generation on defects. Numerical methods like the finite element method (FEM) and the boundary element method (BEM) can overcome these limitations of approximate models. Commercial softwares such as Abaqus FEA and PZFlex use FEM, while CIVA has a 2D FEM solver [1-3]. In this work, we study the performance of the Nyström method (NM) [4,5], an alternative boundary integral equation solver to the BEM, in modeling ultrasonic scattering from defects. To handle larger problems, the Nyström method is accelerated by the multilevel fast multipole algorithm (MLFMA). We apply the NM to benchmark problems and compare its predictions with those of exact and approximate analytical models as well as with experimental results from the World Federation of NDE Centers (WFNDEC). Several examples will be presented to demonstrate the prediction of creeping waves by the NM while also illustrating its improved accuracy over the Kirchhoff approximation. We will conclude with a discussion on the validity and limitations of the NM in modelling practical NDE problems
The Model Inversion Eavesdropping Attack in Semantic Communication Systems
In recent years, semantic communication has been a popular research topic for
its superiority in communication efficiency. As semantic communication relies
on deep learning to extract meaning from raw messages, it is vulnerable to
attacks targeting deep learning models. In this paper, we introduce the model
inversion eavesdropping attack (MIEA) to reveal the risk of privacy leaks in
the semantic communication system. In MIEA, the attacker first eavesdrops the
signal being transmitted by the semantic communication system and then performs
model inversion attack to reconstruct the raw message, where both the white-box
and black-box settings are considered. Evaluation results show that MIEA can
successfully reconstruct the raw message with good quality under different
channel conditions. We then propose a defense method based on random
permutation and substitution to defend against MIEA in order to achieve secure
semantic communication. Our experimental results demonstrate the effectiveness
of the proposed defense method in preventing MIEA.Comment: Accepted by 2023 IEEE Global Communications Conference (GLOBECOM
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