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In this paper, we study the queue-overflow probability of wireless scheduling algorithms. In wireless networks operated under queue-length-based scheduling algorithms, there often exists a tight coupling between the service-rate p...
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In this paper, we study the queue-overflow probability of wireless scheduling algorithms. In wireless networks operated under queue-length-based scheduling algorithms, there often exists a tight coupling between the service-rate process, the system backlog process, the arrival process, and the stochastic process governing channel variations. Although one can use sample-path large-deviation techniques to form an estimate of the queue-overflow probability, the formulation leads to a difficult multidimensional calculus-of-variations problem. In this paper, we present a new technique to address this complexity issue. Using ideas from the Lyapunov function approach in control theory, this technique maps the complex multidimensional calculus-of-variations problem to a 1-D calculus-of-variations problem, and the latter is often much easier to solve. Further, under appropriate conditions, we show that when a scheduling algorithm minimizes the drift of a Lyapunov function at each point of every fluid sample path, the algorithm will be optimal in the sense that it maximizes the asymptotic decay rate of the probability that the Lyapunov function value exceeds a given threshold. We believe that these results can potentially be used to study the queue-overflow probability of a large class of wireless scheduling algorithms and to design new scheduling algorithms with optimal overflow probabilities.
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We propose a novel space-division-based network-coding scheme for multiple-input multiple-output (MIMO) two-way relay channels (TWRCs), in which two multiantenna users exchange information via a multiantenna relay. In the proposed...
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We propose a novel space-division-based network-coding scheme for multiple-input multiple-output (MIMO) two-way relay channels (TWRCs), in which two multiantenna users exchange information via a multiantenna relay. In the proposed scheme, the overall signal space at the relay is divided into two subspaces. In one subspace, the spatial streams of the two users have nearly orthogonal directions and are completely decoded at the relay. In the other subspace, the signal directions of the two users are nearly parallel, and linear functions of the spatial streams are computed at the relay, following the principle of physical-layer network coding. Based on the recovered messages and message-functions, the relay generates and forwards network-coded messages to the two users. We show that, at high signal-to-noise ratio, the proposed scheme achieves the asymptotic sum-rate capacity of the MIMO TWRC within $ {{ 1}over { 2}}log (5/4)approx 0.161$ bits per user-antenna, for any antenna configuration and any channel realization. We perform large-system analysis to derive the average sum-rate of the proposed scheme over Rayleigh-fading MIMO TWRCs. We show that the average asymptotic sum-rate gap to the capacity is at most 0.053 bits per relay-antenna. It is demonstrated that the proposed scheme significantly outperforms the existing schemes.
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The aim of this paper is to propose a more practical mountain fire spread model for fire behavior prediction and management in Southwest forest area of China. These areas are covered mainly with spatial heterogeneous flammable for...
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The aim of this paper is to propose a more practical mountain fire spread model for fire behavior prediction and management in Southwest forest area of China. These areas are covered mainly with spatial heterogeneous flammable forest and are characterized by undulating terrain and steep slopes. This model can produce more accurate fire propagation maps by combining CA (Cellular Automaton) framework with Wang Zhengfei fire physical velocity model in fine scale. Considering the inherent uncertainties of fire propagation, the model has been built on multi-dimension geophysical and environmental components and also sound knowledge of fire spread physical mechanism. Regarding small fuel patches as spatial homogenous cells, this approach makes it easier to generate higher level complex fire behavior maps from CA simple local rules and local behavior integrated with high resolution vegetation images, fine scale terrain maps and surface wind field. Because the model focuses primarily on the study of surface fire front propagation behavior, it attempts to simplify complex fuel modeling. Additionally, this Wang-Geophysical-CA model is able to analyze the time series spatial pattern of fire-front spread and model local behavior instead of the final fire spread pattern of the conventional approach. In this work, not only single influence verification tests have been made, but also simulation tests with multiple influences are carried out to demonstrate the capability of the model with fine scale vegetation maps, surface wind field, terrain, moisture content and man-made structures.
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Vehicular communications networks are envisioned for the access to drive-thru Internet and IP-based infotainment applications. These services are supported by roadside access routers (ARs) that connect vehicular ad hoc networks (V...
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Vehicular communications networks are envisioned for the access to drive-thru Internet and IP-based infotainment applications. These services are supported by roadside access routers (ARs) that connect vehicular ad hoc networks (VANETs) to external IP networks. However, VANETs suffer from asymmetric links due to variable transmission ranges caused by mobility, obstacles, and dissimilar transmission power, which make it difficult to maintain the bidirectional connections and to provide the IP mobility required by most IP applications. Moreover, vehicular mobility results in short-lived connections to the AR, affecting the availability of IP services in VANETs. In this paper, we study the secure and timely handover of IP services in an asymmetric VANET and propose a multihop-authenticated Proxy Mobile IP (MA-PMIP) scheme. MA-PMIP provides an enhanced IP mobility scheme over infrastructure-to-vehicle-to-vehicle (I2V2V) communications that uses location and road traffic information. The MA-PMIP also reacts, depending on the bidirectionality of links, to improve availability of IP services. Moreover, our scheme ensures that the handover signaling is authenticated when V2V paths are employed to reach the infrastructure so that possible attacks are mitigated without affecting the performance of the ongoing sessions. Both analysis and extensive simulations in OMNeT++ are conducted, and the results demonstrate that the MA-PMIP improves service availability and provides secure seamless access to IP applications in asymmetric VANETs.
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Robust detection and tracking of multiple people in cluttered and crowded scenes with severe occlusion is a significant challenge for many computer vision applications. In this paper, we present a novel hybrid synthetic aperture i...
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Robust detection and tracking of multiple people in cluttered and crowded scenes with severe occlusion is a significant challenge for many computer vision applications. In this paper, we present a novel hybrid synthetic aperture imaging model to solve this problem. The main characteristics of this approach are as follows. 1) To the best of our knowledge, this is the first attempt to solve the occluded people imaging and tracking problem in a joint multiple camera synthetic aperture imaging domain. 2) A multiple model framework is designed to achieve seamless interaction among the detection, imaging and tracking modules. 3) In the object detection module, a multiple constraints-based approach is presented for people localization and ghost objects removal in a 3-D foreground silhouette synthetic aperture imaging volume. 4) In the synthetic imaging module, a novel occluder removal-based synthetic imaging approach is proposed to significantly improve the imaging quality of objects even under severe occlusion. 5) In the object tracking module, a camera array is used for robust people tracking in color synthetic aperture images. A network-camera-based hybrid synthetic aperture imaging system has been set up, and experimental results with qualitative and quantitative analyses demonstrate that the method can reliably locate and see people in challenging scenes.
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A novel parallel spectral clustering approach is proposed by exploiting the distributed computing in MATLAB for SAR image segmentation quickly and accurately. For large-scale data applications, most existing spectral clustering al...
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A novel parallel spectral clustering approach is proposed by exploiting the distributed computing in MATLAB for SAR image segmentation quickly and accurately. For large-scale data applications, most existing spectral clustering algorithms suffer from the bottleneck problems of high computational complexity and large memory use. And in the absence of advanced hardware and software equipments with only the loosely coupled computer resources accessible, the framework of MATLAB Parallel Computing-based sparse spectral clustering is constructed in this paper. In the proposed frame, we use a distributed parallel computing model to accelerate computation, where each partition of data instances is assigned to different processor nodes for the similarity matrix calculation in spectral clustering. Further, by the construction of exact t-nearest neighbor sparse symmetric similarity matrix, the sparseness technique is employed to alleviate the storage stress. Besides, the problems of how to choose the number of nearest neighbors and the scaling parameter are also discussed. The segmentation results on artificial synthesis texture images and SAR images show that the proposed parallel algorithm can effectively handle large-size segmentation cases. Meanwhile, it can obtain better segmentation results compared with Nyström approximation spectral clustering and k-means clustering algorithm.
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This paper discusses wide range soft switching solutions to a pulse width modulation (PWM) three-level (TL) dc–dc converter suitable for industrial applications, and proposes four kinds of new PWM TL dc–dc converters. The presen...
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This paper discusses wide range soft switching solutions to a pulse width modulation (PWM) three-level (TL) dc–dc converter suitable for industrial applications, and proposes four kinds of new PWM TL dc–dc converters. The presented topologies have the following desirable features: all switches in each circuit sustain only half of the input voltage; off state voltage of the switches is directly clamped by the input capacitors and no added primary clamping devices, such as clamping diodes, flying capacitors, are required; and phase shifted control method can be used to achieve wide output range. The leading switches in the converters can only realize zero-voltage switching (ZVS), while the lagging switches can obtain ZVS or zero-current switching in different converters. Principle of operation and theoretical analysis are discussed. Experimental results are included to verify the feasibility and advantages of the new topologies.
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Cooperative spectrum sensing (CSS) is a promising technique in cognitive radio networks (CRNs) that utilises multiuser diversity to mitigate channel instability and noise uncertainty. In this study, the relationship between 'coope...
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Cooperative spectrum sensing (CSS) is a promising technique in cognitive radio networks (CRNs) that utilises multiuser diversity to mitigate channel instability and noise uncertainty. In this study, the relationship between 'cooperation mechanisms' and 'spatial-spectral diversity' over multiple channels jointly sensing is investigated in the presence of an imperfect reporting channel. The multiple channels are sensed at the receiver built on the filter bank-based multi-carrier system. The multi-channel CSS strategies are modelled by the introduced 'cooperative ratio' to balance the requirements on 'sensing accuracy', 'efficiency' and 'overhead', which is quantitatively characterised by the energy consumption. The target of CSS is to maximise the aggregate opportunistic throughput of secondary users (SUs) by jointly considering constraints on sensing overhead and the aggregate interference to primary users (PUs). The optimisation is divided into two sequential suboptimisation processes, 'multi-user diversity optimisation' and 'multi-channel diversity optimisation'. An approach is developed from generic algorithms to solve the two sub-problems. Numerical results show that the optimal CSS scheme is effective in improving channel utilisation for SUs with low interference to PUs. This study establishes a valuable cooperative model for the design of multi-channel spectrum sensing algorithms in CRNs.
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It is well known that a multi-agent system (MAS) is a specific system consisting of multiple interacting autonomous agents. Consensus or synchronization, as one of the typical collective behaviors, is ubiquitous in nature. Over th...
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It is well known that a multi-agent system (MAS) is a specific system consisting of multiple interacting autonomous agents. Consensus or synchronization, as one of the typical collective behaviors, is ubiquitous in nature. Over the last decades, consensus has been widely investigated in various disciplines, including mathematics, physics, biology, engineering, and social sciences. In particular, consensus of MAS with dynamical topology is an emerging new topic motivated by many real-world applications, such as wireless communication and sensor networks. However, the collective behavior of MAS with dynamical topology is very complex and cannot be easily analyzed by the traditional approaches. To resolve the issue of dynamical topology, various techniques and methods have been developed in the last decade. This paper aims to review the main advances in the consensus of MAS with dynamical topology, including several fundamental models and the corresponding methods. The main purpose is to promote this emerging topic on multi-agent systems, with emphasis on the interdisciplinary interest from the circuits and systems engineering communities.
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The purpose of this study is to validate a neuromechanical model of the virtual arm (VA) by comparing emerging behaviors of the model to those of experimental observations. Hand stiffness of the VA model was obtained by either the?Pub>...
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The purpose of this study is to validate a neuromechanical model of the virtual arm (VA) by comparing emerging behaviors of the model to those of experimental observations. Hand stiffness of the VA model was obtained by either theoretical computation or simulated perturbations. Variability in hand position of the VA was generated by adding signal dependent noise (SDN) to the motoneuron pools of muscles. Reflex circuits of Ia, Ib and Renshaw cells were included to regulate the motoneuron pool outputs. Evaluation of hand stiffness and variability was conducted in simulations with and without afferent feedback under different patterns of muscle activations during postural maintenance. The simulated hand stiffness and variability ellipses captured the experimentally observed features in shape, magnitude and orientation. Steady state afferent feedback contributed significantly to the increase in hand stiffness by $35.75pm 16.99hbox{%}$ in area, $18.37pm 7.80hbox{%}$ and $16.15pm 7.15hbox{%}$ in major and minor axes; and to the reduction of hand variability by $49.41pm 21.19hbox{%}$ in area, $36.89pm 12.78hbox{%}$ and $18.87pm 23.32hbox{%}$ in major and minor axes. The VA model reproduced the neuromechanical behaviors that were consistent with experimental data, and it could be a useful tool for study of neural control of posture and movement, as well as for application to rehabilitation.
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