4,660 research outputs found

    Secrecy Wireless Information and Power Transfer in Fading Wiretap Channel

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    Simultaneous wireless information and power transfer (SWIPT) has recently drawn significant interests for its dual use of radio signals to provide wireless data and energy access at the same time. However, a challenging secrecy communication issue arises as the messages sent to the information receivers (IRs) may be eavesdropped by the energy receivers (ERs), which are presumed to harvest energy only from the received signals. To tackle this problem, we propose in this paper an artificial noise (AN) aided transmission scheme to facilitate the secrecy information transmission to IRs and yet meet the energy harvesting requirement for ERs, under the assumption that the AN can be cancelled at IRs but not at ERs. Specifically, the proposed scheme splits the transmit power into two parts, to send the confidential message to the IR and an AN to interfere with the ER, respectively. Under a simplified three-node wiretap channel setup, the transmit power allocations and power splitting ratios over fading channels are jointly optimized to minimize the outage probability for delay-limited secrecy information transmission, or to maximize the average rate for no-delay-limited secrecy information transmission, subject to a combination of average and peak power constraints at the transmitter as well as an average energy harvesting constraint at the ER. Both the secrecy outage probability minimization and average rate maximization problems are shown to be non-convex, for each of which we propose the optimal solution based on the dual decomposition as well as suboptimal solution based on the alternating optimization. Furthermore, two benchmark schemes are introduced for comparison. Finally, the performances of proposed schemes are evaluated by simulations in terms of various trade-offs for wireless (secrecy) information versus energy transmissions.Comment: to appear in IEEE Transactions on Vehicular Technolog

    Spiking-Diffusion: Vector Quantized Discrete Diffusion Model with Spiking Neural Networks

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    Spiking neural networks (SNNs) have tremendous potential for energy-efficient neuromorphic chips due to their binary and event-driven architecture. SNNs have been primarily used in classification tasks, but limited exploration on image generation tasks. To fill the gap, we propose a Spiking-Diffusion model, which is based on the vector quantized discrete diffusion model. First, we develop a vector quantized variational autoencoder with SNNs (VQ-SVAE) to learn a discrete latent space for images. With VQ-SVAE, image features are encoded using both the spike firing rate and postsynaptic potential, and an adaptive spike generator is designed to restore embedding features in the form of spike trains. Next, we perform absorbing state diffusion in the discrete latent space and construct a diffusion image decoder with SNNs to denoise the image. Our work is the first to build the diffusion model entirely from SNN layers. Experimental results on MNIST, FMNIST, KMNIST, and Letters demonstrate that Spiking-Diffusion outperforms the existing SNN-based generation model. We achieve FIDs of 37.50, 91.98, 59.23 and 67.41 on the above datasets respectively, with reductions of 58.60\%, 18.75\%, 64.51\%, and 29.75\% in FIDs compared with the state-of-art work.Comment: Under Revie

    Surgery for Complete Vertical Rectus Paralysis Combined with Horizontal Strabismus

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    Aims. To report outcomes of the simultaneous surgical correction of vertical rectus paralysis combined with moderate-to-large angle horizontal strabismus. Methods. If a preoperative forced duction test was positive, antagonist muscle weakening surgery was performed, and then augmented partial rectus muscle transposition (APRMT) + partial horizontal rectus recession-resection was performed 2 months later. If a preoperative forced duction test was negative, APRMT + partial horizontal rectus recession-resection was performed. Antagonistic muscle weakening surgery and/or conventional recession-resection of the horizontal and/or vertical muscles of the contralateral eye was performed 2 months later, as needed. Results. Ten patients with a mean age of 22.3 ± 13.0 years were included and mean follow-up was 7.1 months. The mean vertical deviation that APRMT corrected was 21.4 ± 3.7 PD (prism diopter). The absolute deviation in horizontal significantly decreased from a preoperative value of 48.5 ± 27.4 PD to a value of 3.0 ± 2.3 PD 6 months postoperatively. The movement score decreased from a value of −5 ± 0 preoperatively to a value of −2.7 ± 0.8 at 6 months postoperatively. Conclusion. For patients with complete vertical rectus paralysis combined with a moderate- to-large angle of horizontal strabismus, combined APRMT and partial horizontal rectus recession-resection is safe and effective for correcting vertical and horizontal strabismus

    A Bilevel Game-Theoretic Decision-Making Framework for Strategic Retailers in Both Local and Wholesale Electricity Markets

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    This paper proposes a bilevel game-theoretic model for multiple strategic retailers participating in both wholesale and local electricity markets while considering customers\u27 switching behaviors. At the upper level, each retailer maximizes its own profit by making optimal pricing decisions in the retail market and bidding decisions in the day-ahead wholesale (DAW) and local power exchange (LPE) markets. The interaction among multiple strategic retailers is formulated using the Bertrand competition model. For the lower level, there are three optimization problems. First, the welfare maximization problem is formulated for customers to model their switching behaviors among different retailers. Second, a market-clearing problem is formulated for the independent system operator (ISO) in the DAW market. Third, a novel LPE market is developed for retailers to facilitate their power balancing. In addition, the bilevel multi-leader multi-follower Stackelberg game forms an equilibrium problem with equilibrium constraints (EPEC) problem, which is solved by the diagonalization algorithm. Numerical results demonstrate the feasibility and effectiveness of the EPEC model and the importance of modeling customers\u27 switching behaviors. We corroborate that incentivizing customers\u27 switching behaviors and increasing the number of retailers facilitates retail competition, which results in reducing strategic retailers\u27 retail prices and profits. Moreover, the relationship between customers\u27 switching behaviors and welfare is reflected by a balance between the electricity purchasing cost (i.e., electricity price) and the electricity consumption level
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