Practical Non-Linear Energy Harvesting Model and Resource Allocation for SWIPT Systems

Boshkovska, Elena; Ng, Derrick Wing Kwan; Zlatanov, Nikola; Schober, Robert

doi:10.1109/lcomm.2015.2478460

Cited by 934 publications

(862 citation statements)

References 52 publications

(82 reference statements)

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“…Thus, (47) fulfills all the assumptions of Proposition 3 with respect to (46), which completes the proof of this proposition.…”

Section: A Gee Maximizationsupporting

confidence: 68%

“…Nevertheless, the proposed monotonic fractional programming framework can also be used to solve WSEE and WPEE maximization problems 2 . To 2 Alternative approaches for the maximization of sum-of-ratios problems have recently appeared in [45], [46] begin with, observe that the WSEE can be expressed as a single ratio:…”

Section: Wsee and Wpee Maximizationmentioning

confidence: 99%

“…As pointed out in Section III-A, this prevents from directly using fractional programming to solve (46). To circumvent this issue, we exploit its hidden structure and obtain the following main result:…”

Section: A Gee Maximizationmentioning

confidence: 99%

See 2 more Smart Citations

Globally Optimal Energy-Efficient Power Control and Receiver Design in Wireless Networks

Zappone

Björnson

Sanguinetti

et al. 2017

IEEE Trans. Signal Process.

237

228

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Abstract-The characterization of the global maximum of energy efficiency (EE) problems in wireless networks is a challenging problem due to the non-convex nature of investigated problems in interference channels. The aim of this work is to develop a new and general framework to achieve globally optimal solutions. First, the hidden monotonic structure of the most common EE maximization problems is exploited jointly with fractional programming theory to obtain globally optimal solutions with exponential complexity in the number of network links. To overcome this issue, we also propose a framework to compute suboptimal power control strategies characterized by affordable complexity. This is achieved by merging fractional programming and sequential optimization. The proposed monotonic framework is used to shed light on the ultimate performance of wireless networks in terms of EE and also to benchmark the performance of the lower-complexity framework based on sequential programming. Numerical evidence is provided to show that the sequential fractional programming framework achieves global optimality in several practical communication scenarios.

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“…Thus, (47) fulfills all the assumptions of Proposition 3 with respect to (46), which completes the proof of this proposition.…”

Section: A Gee Maximizationsupporting

confidence: 68%

Section: Wsee and Wpee Maximizationmentioning

confidence: 99%

See 1 more Smart Citation

Globally Optimal Energy-Efficient Power Control and Receiver Design in Wireless Networks

Zappone

Björnson

Sanguinetti

et al. 2017

IEEE Trans. Signal Process.

237

228

View full text Add to dashboard Cite

show abstract

“…However, in practice, the power conversion efficiency is greatly relative to the input power level and the EH circuits generally result in a nonlinear end-to-end wireless power transfer. According to the practical nonlinear EH model given by [18], the harvested energy Φ ER at the ER is typically modeled as…”

Section: Energy-harvesting Modelmentioning

confidence: 99%

Energy Efficiency Design for Secure MISO Cognitive Radio Network Based on a Nonlinear EH Model

et al. 2018

Mathematical Problems in Engineering

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In this work, we investigate the secrecy energy efficiency (SEE) optimization problem for a multiple-input single-output (MISO) cognitive radio (CR) network based on a practical nonlinear energy-harvesting (EH) model. In particular, the energy receiver (ER) is assumed to be a potential eavesdropper due to the open architecture of a CR network with simultaneous wireless information and power transfer (SWIPT), such that the confidential message is prone to be intercepted in wireless communications. The aim of this work is to provide a secure transmit beamforming design while satisfying the minimum secrecy rate target, the minimum EH requirement, and the maximum interference leakage power to primary user (PU). In addition, we consider that all the channel state information (CSI) is perfectly known at the secondary transmitter (ST). We formulate this beamforming design as a SEE maximization problem; however, the original optimization problem is not convex due to the nonlinear fractional objective function. To solve it, a novel iterative algorithm is proposed to obtain the globally optimal solution of the primal problem by using the nonlinear fractional programming and sequential programming. Finally, numerical simulation results are presented to validate the performance of the proposed scheme.

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“…An analysis of the impact of the CCI on an amplify-and-forward (AF) relay network was later provided in [18]. However, both papers considered the linear energy harvester model, which might be impractical in realistic scenarios owing to the nonlinearities of the electronic components, as recently reported in [19], [20]. Analyses of AF and DF relaying networks with a nonlinear model were provided in [21] and [22], respectively.…”

Section: Introductionmentioning

confidence: 99%

Performance Analysis of Nonlinear Energy-Harvesting DF Relay System in Interference-Limited Nakagami-m Fading Environment

Cvetković¹,

Blagojević²,

Ivaniš³

2017

ETRI Journal

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A decode-and-forward system with an energyharvesting relay is analyzed for the case when an arbitrary number of independent interference signals affect the communication at both the relay and the destination nodes. The scenario in which the relay harvests energy from both the source and interference signals using a time switching scheme is analyzed. The analysis is performed for the interference-limited Nakagami-m fading environment, assuming a realistic nonlinearity for the electronic devices. The closed-form outage probability expression for the system with a nonlinear energy harvester is derived. An asymptotic expression valid for the case of a simpler linear harvesting model is also provided. The derived analytical results are corroborated by an independent simulation model. The impacts of the saturation threshold power, the energy-harvesting ratio, and the number and power of the interference signals on the system performance are analyzed.

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Practical Non-Linear Energy Harvesting Model and Resource Allocation for SWIPT Systems

Cited by 934 publications

References 52 publications

Globally Optimal Energy-Efficient Power Control and Receiver Design in Wireless Networks

Globally Optimal Energy-Efficient Power Control and Receiver Design in Wireless Networks

Energy Efficiency Design for Secure MISO Cognitive Radio Network Based on a Nonlinear EH Model

Performance Analysis of Nonlinear Energy-Harvesting DF Relay System in Interference-Limited Nakagami-m Fading Environment

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