3,342 research outputs found

    Spatial Throughput Maximization of Wireless Powered Communication Networks

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    Wireless charging is a promising way to power wireless nodes' transmissions. This paper considers new dual-function access points (APs) which are able to support the energy/information transmission to/from wireless nodes. We focus on a large-scale wireless powered communication network (WPCN), and use stochastic geometry to analyze the wireless nodes' performance tradeoff between energy harvesting and information transmission. We study two cases with battery-free and battery-deployed wireless nodes. For both cases, we consider a harvest-then-transmit protocol by partitioning each time frame into a downlink (DL) phase for energy transfer, and an uplink (UL) phase for information transfer. By jointly optimizing frame partition between the two phases and the wireless nodes' transmit power, we maximize the wireless nodes' spatial throughput subject to a successful information transmission probability constraint. For the battery-free case, we show that the wireless nodes prefer to choose small transmit power to obtain large transmission opportunity. For the battery-deployed case, we first study an ideal infinite-capacity battery scenario for wireless nodes, and show that the optimal charging design is not unique, due to the sufficient energy stored in the battery. We then extend to the practical finite-capacity battery scenario. Although the exact performance is difficult to be obtained analytically, it is shown to be upper and lower bounded by those in the infinite-capacity battery scenario and the battery-free case, respectively. Finally, we provide numerical results to corroborate our study.Comment: 15 double-column pages, 8 figures, to appear in IEEE JSAC in February 2015, special issue on wireless communications powered by energy harvesting and wireless energy transfe

    Capacity of UAV-Enabled Multicast Channel: Joint Trajectory Design and Power Allocation

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    This paper studies an unmanned aerial vehicle (UAV)-enabled multicast channel, in which a UAV serves as a mobile transmitter to deliver common information to a set of KK ground users. We aim to characterize the capacity of this channel over a finite UAV communication period, subject to its maximum speed constraint and an average transmit power constraint. To achieve the capacity, the UAV should use a sufficiently long code that spans over its whole communication period. Accordingly, the multicast channel capacity is achieved via maximizing the minimum achievable time-averaged rates of the KK users, by jointly optimizing the UAV's trajectory and transmit power allocation over time. However, this problem is non-convex and difficult to be solved optimally. To tackle this problem, we first consider a relaxed problem by ignoring the maximum UAV speed constraint, and obtain its globally optimal solution via the Lagrange dual method. The optimal solution reveals that the UAV should hover above a finite number of ground locations, with the optimal hovering duration and transmit power at each location. Next, based on such a multi-location-hovering solution, we present a successive hover-and-fly trajectory design and obtain the corresponding optimal transmit power allocation for the case with the maximum UAV speed constraint. Numerical results show that our proposed joint UAV trajectory and transmit power optimization significantly improves the achievable rate of the UAV-enabled multicast channel, and also greatly outperforms the conventional multicast channel with a fixed-location transmitter.Comment: To appear in the IEEE International Conference on Communications (ICC), 201

    The mechanical energy input to the ocean induced by tropical cyclones

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    Author Posting. © American Meteorological Society, 2008. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Physical Oceanography 38 (2008): 1253-1266, doi:10.1175/2007JPO3786.1.Wind stress and tidal dissipation are the most important sources of mechanical energy for maintaining the oceanic general circulation. The contribution of mechanical energy due to tropical cyclones can be a vitally important factor in regulating the oceanic general circulation and its variability. However, previous estimates of wind stress energy input were based on low-resolution wind stress data in which strong nonlinear events, such as tropical cyclones, were smoothed out. Using a hurricane–ocean coupled model constructed from an axisymmetric hurricane model and a three-layer ocean model, the rate of energy input to the world’s oceans induced by tropical cyclones over the period from 1984 to 2003 was estimated. The energy input is estimated as follows: 1.62 TW to the surface waves and 0.10 TW to the surface currents (including 0.03 TW to the near-inertial motions). The rate of gravitational potential energy increase due to tropical cyclones is 0.05 TW. Both the energy input from tropical cyclones and the increase of gravitational potential energy of the ocean show strong interannual and decadal variability with an increasing rate of 16% over the past 20 years. The annual mean diapycnal upwelling induced by tropical cyclones over the past 20 years is estimated as 39 Sv (Sv ≡ 106 m3 s−1). Owing to tropical cyclones, diapycnal mixing in the upper ocean (below the mixed layer) is greatly enhanced. Within the regimes of strong activity of tropical cyclones, the increase of diapycnal diffusivity is on the order of (1 − 6) × 10−4 m2 s−1. The tropical cyclone–related energy input and diapycnal mixing may play an important role in climate variability, ecology, fishery, and environments.LLL and WW were supported by the National Basic Research Priorities Programmer of China through Grant 2007CB816004 and National Outstanding Youth Natural Science Foundation of China FIG. 15. Annual-mean vertical diffusivity induced by tropical cyclones from 1984 to 2003 (units: 10 4 m2 s 1): (right) the horizontal distribution and (left) the zonally averaged vertical diffusivity. JUNE 2008 L IU ET AL . 1265 under Grant 40725017. RXH was supported by the W. Alan Clark Chair from Woods Hole Oceanographic Institution
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