2018
DOI: 10.1109/jsyst.2017.2771480
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Optimization of Links With a Battery-Assisted Time-Switching Wireless Energy Harvesting Relay

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Cited by 15 publications
(14 citation statements)
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“…In our considered system, the relay not only runs out of the harvested energy, but also may extract the energy E b (E b ≥ 0) from its battery. Let us focus on the worst case scenario where Rayleigh fading is used to model small-scale fading over each channel [8,[10][11][12][16][17][18][19], and we assume that the small-scale fading follows a complex Gaussian distribution with zero mean and unit variance. Hence, the k-th The relay follows the PS scheme in which each transmission slot is divided into two equal sub-slots.…”
Section: System Modelmentioning
confidence: 99%
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“…In our considered system, the relay not only runs out of the harvested energy, but also may extract the energy E b (E b ≥ 0) from its battery. Let us focus on the worst case scenario where Rayleigh fading is used to model small-scale fading over each channel [8,[10][11][12][16][17][18][19], and we assume that the small-scale fading follows a complex Gaussian distribution with zero mean and unit variance. Hence, the k-th The relay follows the PS scheme in which each transmission slot is divided into two equal sub-slots.…”
Section: System Modelmentioning
confidence: 99%
“…After solving the internal integral with respect to the variable y, (18) can be obtained. Since the integral is unbounded and there is no closed-form for (18), we use the variable substitution y = tanθ and adopt the Gaussian-Chebyshev quadrature (in this paper, we adopt the Gaussian-Chebyshev quadrature instead of other approximation methods because it can provide sufficient level of accuracy with very few terms; thanks to this advantage, the Gaussian-Chebyshev quadrature has been widely used in the state-of-the-art works [11,12,21]) to approximate Systems (18) as (19), where…”
Section: Ergodic Capacitymentioning
confidence: 99%
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