The Experts below are selected from a list of 264309 Experts worldwide ranked by ideXlab platform
Robert Schober - One of the best experts on this subject based on the ideXlab platform.
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relay selection for simultaneous information transmission and wireless energy transfer a Tradeoff perspective
IEEE Journal on Selected Areas in Communications, 2015Co-Authors: Diomidis S Michalopoulos, Himal A Suraweera, Robert SchoberAbstract:In certain applications, relay terminals can be employed to simultaneously deliver information and energy to a designated receiver and a set of radio frequency (RF) energy harvesters, respectively. In such scenarios, the relay that is preferable for information transmission does not necessarily coincide with the relay that is preferable for energy transfer, since the corresponding channels fade independently. Relay selection thus entails a Tradeoff between the efficiency of the information transmission to the receiver and the amount of energy transferred to the energy harvesters. The study of this Tradeoff is the subject on which this work mainly focuses. Specifically, we investigate the dependence of the ergodic capacity and the outage probability of the information transmission to the receiver on the amount of energy transferred to the RF energy harvesters. We propose a relay selection policy that yields the optimal Tradeoff in a maximum capacity/minimum outage probability sense, for a given energy transfer constraint. We also propose two suboptimal relay selection methods that apply to scenarios with limited availability of channel state information. Additionally, we propose a suboptimal scheme which approximates the optimal scheme for the special case of two relays and facilitates performance analysis. Interesting insights on the aforementioned Tradeoffs are unveiled.
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relay selection for simultaneous information transmission and wireless energy transfer a Tradeoff perspective
arXiv: Information Theory, 2013Co-Authors: Diomidis S Michalopoulos, Himal A Suraweera, Robert SchoberAbstract:In certain applications, relay terminals can be employed to simultaneously deliver information and energy to a designated receiver and a radio frequency (RF) energy harvester, respectively. In such scenarios, the relay that is preferable for information transmission does not necessarily coincide with the relay with the strongest channel to the energy harvester, since the corresponding channels fade independently. Relay selection thus entails a Tradeoff between the efficiency of the information transfer to the receiver and the amount of energy transferred to the energy harvester. The study of this Tradeoff is the subject on which this work mainly focuses. Specifically, we investigate the behavior of the ergodic capacity and the outage probability of the information transmission to the receiver, for a given amount of energy transferred to the RF energy harvester. We propose two relay selection methods that apply to any number of available relays. Furthermore, for the case of two relays, we develop the optimal relay selection method in a maximum capacity / minimum outage probability sense, for a given energy transfer constraint. A close-to-optimal selection method that is easier to analyze than the optimal one is also examined. Closed-form expressions for the capacity-energy and the outage-energy Tradeoffs of the developed schemes are provided and corroborated by simulations. Interesting insights on the aforementioned Tradeoffs are obtained.
Jae-mo Kang - One of the best experts on this subject based on the ideXlab platform.
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Wireless Information and Power Transfer: Rate-Energy Tradeoff for Nonlinear Energy Harvesting
IEEE Transactions on Wireless Communications, 2018Co-Authors: Jae-mo KangAbstract:In this paper, we study rate-energy (R-E) Tradeoffs for simultaneous wireless information and power transfer (SWIPT). In the existing literature, by invoking a simplistic and ideal assumption of linear energy harvesting, the R-E Tradeoff performance was analyzed only for the four SWIPT schemes: the dynamic power splitting, type-I on-off power splitting (OPS), static power splitting, and time switching. Different from such works, in this work, we consider the realistic and practical scenario of nonlinear energy harvesting. Furthermore, to characterize the R-E Tradeoff with nonlinear energy harvesting, we propose a new SWIPT scheme, the generalized OPS (GOPS). As a special case of the proposed GOPS, we also investigate an additional SWIPT scheme, the type-II OPS. Through the analysis based on the realistic nonlinear models reported in the literature, we derive new theoretical results on the R-E Tradeoff, which are in sharp contrast to those in the existing literature obtained with linear energy harvesting. Furthermore, we provide various useful insights into the SWIPT system with nonlinear energy harvesting.
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Rate-Energy Tradeoff and Decoding Error Probability-Energy Tradeoff for SWIPT in Finite Code Length
IEEE Transactions on Wireless Communications, 2017Co-Authors: Jae-mo KangAbstract:In this paper, the fundamental performance of the simultaneous wireless information and power transfer (SWIPT) system is studied. Unlike any existing works where the codelength was assumed to be infinity, we explicitly consider the case of the finite codelength, which is much more realistic especially for the practical SWIPT system due to its limited power and complexity. For the four well-known SWIPT schemes, we analyze the Tradeoff between the rate and energy; then we study the optimality of those SWIPT schemes. Furthermore, to fully characterize the fundamental performance of the SWIPT system in the regime of finite codelength, we propose to additionally use the new Tradeoff between the decoding error probability and the harvested energy. In the sense of this new Tradeoff, we study the optimality of the four SWIPT schemes. For the analysis of the two types of Tradeoffs, we consider two different cases: when the transmit power of symbols is adapted or not. For various scenarios, we provide useful insights into the performance of the SWIPT system in the finite codelength.
Diomidis S Michalopoulos - One of the best experts on this subject based on the ideXlab platform.
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relay selection for simultaneous information transmission and wireless energy transfer a Tradeoff perspective
IEEE Journal on Selected Areas in Communications, 2015Co-Authors: Diomidis S Michalopoulos, Himal A Suraweera, Robert SchoberAbstract:In certain applications, relay terminals can be employed to simultaneously deliver information and energy to a designated receiver and a set of radio frequency (RF) energy harvesters, respectively. In such scenarios, the relay that is preferable for information transmission does not necessarily coincide with the relay that is preferable for energy transfer, since the corresponding channels fade independently. Relay selection thus entails a Tradeoff between the efficiency of the information transmission to the receiver and the amount of energy transferred to the energy harvesters. The study of this Tradeoff is the subject on which this work mainly focuses. Specifically, we investigate the dependence of the ergodic capacity and the outage probability of the information transmission to the receiver on the amount of energy transferred to the RF energy harvesters. We propose a relay selection policy that yields the optimal Tradeoff in a maximum capacity/minimum outage probability sense, for a given energy transfer constraint. We also propose two suboptimal relay selection methods that apply to scenarios with limited availability of channel state information. Additionally, we propose a suboptimal scheme which approximates the optimal scheme for the special case of two relays and facilitates performance analysis. Interesting insights on the aforementioned Tradeoffs are unveiled.
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relay selection for simultaneous information transmission and wireless energy transfer a Tradeoff perspective
arXiv: Information Theory, 2013Co-Authors: Diomidis S Michalopoulos, Himal A Suraweera, Robert SchoberAbstract:In certain applications, relay terminals can be employed to simultaneously deliver information and energy to a designated receiver and a radio frequency (RF) energy harvester, respectively. In such scenarios, the relay that is preferable for information transmission does not necessarily coincide with the relay with the strongest channel to the energy harvester, since the corresponding channels fade independently. Relay selection thus entails a Tradeoff between the efficiency of the information transfer to the receiver and the amount of energy transferred to the energy harvester. The study of this Tradeoff is the subject on which this work mainly focuses. Specifically, we investigate the behavior of the ergodic capacity and the outage probability of the information transmission to the receiver, for a given amount of energy transferred to the RF energy harvester. We propose two relay selection methods that apply to any number of available relays. Furthermore, for the case of two relays, we develop the optimal relay selection method in a maximum capacity / minimum outage probability sense, for a given energy transfer constraint. A close-to-optimal selection method that is easier to analyze than the optimal one is also examined. Closed-form expressions for the capacity-energy and the outage-energy Tradeoffs of the developed schemes are provided and corroborated by simulations. Interesting insights on the aforementioned Tradeoffs are obtained.
Leon Bottou - One of the best experts on this subject based on the ideXlab platform.
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NIPS - The Tradeoffs of Large Scale Learning
2007Co-Authors: Olivier Bousquet, Leon BottouAbstract:This contribution develops a theoretical framework that takes into account the effect of approximate optimization on learning algorithms. The analysis shows distinct Tradeoffs for the case of small-scale and large-scale learning problems. Small-scale learning problems are subject to the usual approximation-estimation Tradeoff. Large-scale learning problems are subject to a qualitatively different Tradeoff involving the computational complexity of the underlying optimization algorithms in non-trivial ways.
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the Tradeoffs of large scale learning
Neural Information Processing Systems, 2007Co-Authors: Olivier Bousquet, Leon BottouAbstract:This contribution develops a theoretical framework that takes into account the effect of approximate optimization on learning algorithms. The analysis shows distinct Tradeoffs for the case of small-scale and large-scale learning problems. Small-scale learning problems are subject to the usual approximation-estimation Tradeoff. Large-scale learning problems are subject to a qualitatively different Tradeoff involving the computational complexity of the underlying optimization algorithms in non-trivial ways.
Peter Kareiva - One of the best experts on this subject based on the ideXlab platform.
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modeling multiple ecosystem services biodiversity conservation commodity production and Tradeoffs at landscape scales
Frontiers in Ecology and the Environment, 2009Co-Authors: Erik J Nelson, Guillermo Mendoza, James Regetz, Stephen Polasky, Heather Tallis, Drichard Cameron, Kai M A Chan, Gretchen C Daily, Joshua Goldstein, Peter KareivaAbstract:Nature provides a wide range of benefits to people. There is increasing consensus about the importance of incorporating these “ecosystem services” into resource management decisions, but quantifying the levels and values of these services has proven difficult. We use a spatially explicit modeling tool, Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST), to predict changes in ecosystem services, biodiversity conservation, and commodity production levels. We apply InVEST to stakeholder-defined scenarios of land-use/land-cover change in the Willamette Basin, Oregon. We found that scenarios that received high scores for a variety of ecosystem services also had high scores for biodiversity, suggesting there is little Tradeoff between biodiversity conservation and ecosystem services. Scenarios involving more development had higher commodity production values, but lower levels of biodiversity conservation and ecosystem services. However, including payments for carbon sequestration alleviates this Tradeoff. Quantifying ecosystem services in a spatially explicit manner, and analyzing Tradeoffs between them, can help to make natural resource decisions more effective, efficient, and defensible.
