3,079 research outputs found

    Random Access Transport Capacity

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    We develop a new metric for quantifying end-to-end throughput in multihop wireless networks, which we term random access transport capacity, since the interference model presumes uncoordinated transmissions. The metric quantifies the average maximum rate of successful end-to-end transmissions, multiplied by the communication distance, and normalized by the network area. We show that a simple upper bound on this quantity is computable in closed-form in terms of key network parameters when the number of retransmissions is not restricted and the hops are assumed to be equally spaced on a line between the source and destination. We also derive the optimum number of hops and optimal per hop success probability and show that our result follows the well-known square root scaling law while providing exact expressions for the preconstants as well. Numerical results demonstrate that the upper bound is accurate for the purpose of determining the optimal hop count and success (or outage) probability.Comment: Submitted to IEEE Trans. on Wireless Communications, Sept. 200

    An Upper Bound on Multi-hop Transmission Capacity with Dynamic Routing Selection

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    This paper develops upper bounds on the end-to-end transmission capacity of multi-hop wireless networks. Potential source-destination paths are dynamically selected from a pool of randomly located relays, from which a closed-form lower bound on the outage probability is derived in terms of the expected number of potential paths. This is in turn used to provide an upper bound on the number of successful transmissions that can occur per unit area, which is known as the transmission capacity. The upper bound results from assuming independence among the potential paths, and can be viewed as the maximum diversity case. A useful aspect of the upper bound is its simple form for an arbitrary-sized network, which allows insights into how the number of hops and other network parameters affect spatial throughput in the non-asymptotic regime. The outage probability analysis is then extended to account for retransmissions with a maximum number of allowed attempts. In contrast to prevailing wisdom, we show that predetermined routing (such as nearest-neighbor) is suboptimal, since more hops are not useful once the network is interference-limited. Our results also make clear that randomness in the location of relay sets and dynamically varying channel states is helpful in obtaining higher aggregate throughput, and that dynamic route selection should be used to exploit path diversity.Comment: 14 pages, 5 figures, accepted to IEEE Transactions on Information Theory, 201

    Loci Controlling Resistance to High Plains Virus and Wheat Streak Mosaic Virus in a B73 Ă— Mo17 Population of Maize

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    High Plains disease has the potential to cause significant yield loss in susceptible corn (Zea mays L.) and wheat (Triticum aestivum L.) genotypes, especially in the central and western USA. The primary causal agent, High Plains virus (HPV), is vectored by wheat curl mite (WCM; Aceria tossicheila Keifer), which is also the vector of wheat streak mosaic virus (WSMV). In general, the two diseases occur together as a mixed infection in the field. The objective of this research was to characterize the inheritance of HPV and WSMV resistance using B73 (resistant to HPV and WSMV) Ă— Mo17 (moderately susceptible to HPV and WSMV) recombinant inbred lines. A population of 129 recombinant inbred lines scored for 167 molecular markers was used to evaluate resistance to WSMV and to a mixed infection of WSMV and HPV. Loci conferring resistance to systemic movement of WSMV in plants mapped to chromosomes 3, 6, and 10, consistent with the map position of wsm2, wsm1, and wsm3, respectively. Major genes for resistance to systemic spread of HPV in doubly infected plants mapped to chromosomes 3 and 6, coincident or tightly linked with the WSMV resistance loci. Analysis of doubly infected plants revealed that chromosome 6 had a major effect on HPV resistance, consistent with our previous analysis of B73 Ă— W64A and B73 Ă— Wf9 populations. Quantitative trait loci (QTL) affecting resistance to localized symptom development mapped to chromosomes 4 (umc66), 5 (bnl5.40), and 6 (umc85), and accounted for 24% of the phenotypic variation. Localized symptoms may reflect the amount of mite feeding or the extent of virus spread at the point of infection. Identification of cosegregating markers may facilitate selection for HPV and WSMV resistance in corn breeding programs

    Parametric Macromodels of Differential Drivers and Receivers

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    This paper addresses the modeling of differential drivers and receivers for the analog simulation of high-speed interconnection systems. The proposed models are based on mathematical expressions, whose parameters can be estimated from the transient responses of the modeled devices. The advantages of this macromodeling approach are: improved accuracy with respect to models based on simplified equivalent circuits of devices; improved numerical efficiency with respect to detailed transistor-level models of devices; hiding of the internal structure of devices; straightforward circuit interpretation; or implementations in analog mixed-signal simulators. The proposed methodology is demonstrated on example devices and is applied to the prediction of transient waveforms and eye diagrams of a typical low-voltage differential signaling (LVDS) data link

    Modeling and Analysis of K-Tier Downlink Heterogeneous Cellular Networks

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    Cellular networks are in a major transition from a carefully planned set of large tower-mounted base-stations (BSs) to an irregular deployment of heterogeneous infrastructure elements that often additionally includes micro, pico, and femtocells, as well as distributed antennas. In this paper, we develop a tractable, flexible, and accurate model for a downlink heterogeneous cellular network (HCN) consisting of K tiers of randomly located BSs, where each tier may differ in terms of average transmit power, supported data rate and BS density. Assuming a mobile user connects to the strongest candidate BS, the resulting Signal-to-Interference-plus-Noise-Ratio (SINR) is greater than 1 when in coverage, Rayleigh fading, we derive an expression for the probability of coverage (equivalently outage) over the entire network under both open and closed access, which assumes a strikingly simple closed-form in the high SINR regime and is accurate down to -4 dB even under weaker assumptions. For external validation, we compare against an actual LTE network (for tier 1) with the other K-1 tiers being modeled as independent Poisson Point Processes. In this case as well, our model is accurate to within 1-2 dB. We also derive the average rate achieved by a randomly located mobile and the average load on each tier of BSs. One interesting observation for interference-limited open access networks is that at a given SINR, adding more tiers and/or BSs neither increases nor decreases the probability of coverage or outage when all the tiers have the same target-SINR.Comment: IEEE Journal on Selected Areas in Communications, vol. 30, no. 3, pp. 550 - 560, Apr. 201

    Application of serious games to sport, health and exercise

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    Use of interactive entertainment has been exponentially expanded since the last decade. Throughout this 10+ year evolution there has been a concern about turning entertainment properties into serious applications, a.k.a "Serious Games". In this article we present two set of Serious Game applications, an Environment Visualising game which focuses solely on applying serious games to elite Olympic sport and another set of serious games that incorporate an in house developed proprietary input system that can detect most of the human movements which focuses on applying serious games to health and exercise

    Dual-Branch MRC Receivers under Spatial Interference Correlation and Nakagami Fading

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    Despite being ubiquitous in practice, the performance of maximal-ratio combining (MRC) in the presence of interference is not well understood. Because the interference received at each antenna originates from the same set of interferers, but partially de-correlates over the fading channel, it possesses a complex correlation structure. This work develops a realistic analytic model that accurately accounts for the interference correlation using stochastic geometry. Modeling interference by a Poisson shot noise process with independent Nakagami fading, we derive the link success probability for dual-branch interference-aware MRC. Using this result, we show that the common assumption that all receive antennas experience equal interference power underestimates the true performance, although this gap rapidly decays with increasing the Nakagami parameter mIm_{\text{I}} of the interfering links. In contrast, ignoring interference correlation leads to a highly optimistic performance estimate for MRC, especially for large mIm_{\text{I}}. In the low outage probability regime, our success probability expression can be considerably simplified. Observations following from the analysis include: (i) for small path loss exponents, MRC and minimum mean square error combining exhibit similar performance, and (ii) the gains of MRC over selection combining are smaller in the interference-limited case than in the well-studied noise-limited case.Comment: to appear in IEEE Transactions on Communication

    Measurement Bounds for Sparse Signal Ensembles via Graphical Models

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    In compressive sensing, a small collection of linear projections of a sparse signal contains enough information to permit signal recovery. Distributed compressive sensing (DCS) extends this framework by defining ensemble sparsity models, allowing a correlated ensemble of sparse signals to be jointly recovered from a collection of separately acquired compressive measurements. In this paper, we introduce a framework for modeling sparse signal ensembles that quantifies the intra- and inter-signal dependencies within and among the signals. This framework is based on a novel bipartite graph representation that links the sparse signal coefficients with the measurements obtained for each signal. Using our framework, we provide fundamental bounds on the number of noiseless measurements that each sensor must collect to ensure that the signals are jointly recoverable.Comment: 11 pages, 2 figure
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