320,634 research outputs found

    Modeling of Si-QD Solar Cell in MATLAB

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    In this paper, the modeling and analysis of single bi-layer Si-QD solar cell is addressed. The modeling of solar cell is done in MATLAB. The photo currents are calculated for various Si-QD diameters like 2.5, 3, 3.5 and 4 nm and SiO2 barrier layer thicknesses like 2.5, 2 and 1.5 nm. It has been observed that with the Si-QD diameter, the photo-current increases. On the other hand, photo-current varies conversely with barrier layer thickness due low carrier tunneling probability through barrier. When you are citing the document, use the following link http://essuir.sumdu.edu.ua/handle/123456789/3100

    Hierarchical Stochastic Block Model for Community Detection in Multiplex Networks

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    Multiplex networks have become increasingly more prevalent in many fields, and have emerged as a powerful tool for modeling the complexity of real networks. There is a critical need for developing inference models for multiplex networks that can take into account potential dependencies across different layers, particularly when the aim is community detection. We add to a limited literature by proposing a novel and efficient Bayesian model for community detection in multiplex networks. A key feature of our approach is the ability to model varying communities at different network layers. In contrast, many existing models assume the same communities for all layers. Moreover, our model automatically picks up the necessary number of communities at each layer (as validated by real data examples). This is appealing, since deciding the number of communities is a challenging aspect of community detection, and especially so in the multiplex setting, if one allows the communities to change across layers. Borrowing ideas from hierarchical Bayesian modeling, we use a hierarchical Dirichlet prior to model community labels across layers, allowing dependency in their structure. Given the community labels, a stochastic block model (SBM) is assumed for each layer. We develop an efficient slice sampler for sampling the posterior distribution of the community labels as well as the link probabilities between communities. In doing so, we address some unique challenges posed by coupling the complex likelihood of SBM with the hierarchical nature of the prior on the labels. An extensive empirical validation is performed on simulated and real data, demonstrating the superior performance of the model over single-layer alternatives, as well as the ability to uncover interesting structures in real networks

    On the Behavior of the Distributed Coordination Function of IEEE 802.11 with Multirate Capability under General Transmission Conditions

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    The aim of this paper is threefold. First, it presents a multi-dimensional Markovian state transition model characterizing the behavior of the IEEE 802.11 protocol at the Medium Access Control layer which accounts for packet transmission failures due to channel errors modeling both saturated and non-saturated traffic conditions. Second, it provides a throughput analysis of the IEEE 802.11 protocol at the data link layer in both saturated and non-saturated traffic conditions taking into account the impact of both the physical propagation channel and multirate transmission in Rayleigh fading environment. The general traffic model assumed is M/M/1/K. Finally, it shows that the behavior of the throughput in non-saturated traffic conditions is a linear combination of two system parameters; the payload size and the packet rates, λ(s)\lambda^{(s)}, of each contending station. The validity interval of the proposed model is also derived. Simulation results closely match the theoretical derivations, confirming the effectiveness of the proposed models.Comment: Submitted to IEEE Transactions on Wireless Communications, October 21, 200

    Acceleration of High-Fidelity Wireless Network Simulations

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    Network simulation with bit-accurate modeling of modulation, coding and channel properties is typically computationally intensive. Simple link-layer models that are frequently used in network simulations sacrifice accuracy to decrease simulation time. We investigate the performance and simulation time of link models that use analytical bounds on link performance and bit-accurate link models executed in Graphical Processing Units (GPUs). We show that properly chosen analytical bounds on link performance can result in simulation results close to those using bit-level simulation while providing a significant reduction in simulation time. We also show that bit-accurate decoding in link models can be expedited using parallel processing in GPUs without compromising accuracy and decreasing the overall simulation time
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