Max-Min Fair Energy Beamforming for Wireless Powered Communication With Non-Linear Energy Harvesting

Cantos, Luiggi; Kim, Yun Hee

doi:10.1109/access.2019.2918649

Cited by 13 publications

(18 citation statements)

References 28 publications

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“…Compared with the sigmoid model with sensitivity of [40], we see that our proposed NLEH model is a bit more accurate in terms of the RMSE. We have observed the same situation with another data set in [23,Fig.…”

Section: Rational Modelmentioning

confidence: 84%

“…The sigmoid model has been modified in [32] to incorporate non-zero sensitivity levels. This modified model has been applied for energy beamforming optimization [40]. The non-linear models of [31] and [32] have been studied in [41].…”

Section: B Energy Harvester Models and Resource Allocationsmentioning

confidence: 99%

“…Resource allocation schemes highly depend on accurate mathematical models for the RF EH circuits and the discrepancy between the properties of practical nonlinear EH circuits and the linear EH model may cause performance degradation in practical implementation due to the drastic resource allocation mismatches [42]. There are a few papers investigating resource allocations for WPCNs with nonlinear EH models [24], [40], [42]. In particular, in [42], with the sigmoid nonlinear EH model, the time allocation and power control of a multi-user WPCN system are jointly optimized to maximize the minimum individual throughput.…”

Section: B Energy Harvester Models and Resource Allocationsmentioning

confidence: 99%

“…The authors in [24] also investigate the optimal time and power allocation of a multi-user TDMA WPCN With the peice-wise linear EH model. Moreover, reference [40] adopts the sigmoid nonlinear EH model with sensitivity and investigates the energy beamforming and time allocation problem to maximize the rate fairness. In this scheme, the hybrid AP supports WPT via energy beamforming and WDT via space-division-multiple-access (SDMA).…”

Section: B Energy Harvester Models and Resource Allocationsmentioning

confidence: 99%

“…. , h K ], to make the input power (P r = Ω 1,k |h H k w| 2 ) as large as possible under the constraint w 2 2 ≤ P t [40], [57]. Therefore, the energy beamformer can be written as w = Fv, where v ∈ C r×1 is a weight vector and matrix F ∈ C N ×r forms an orthonormal basis for the column space of H with r = rank(H)(≤ min(N, K)) and F H F = I. Hence…”

Section: Energy Beamforming Optimizationmentioning

confidence: 99%

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Performance Analysis and Resource Allocations for a WPCN With a New Nonlinear Energy Harvester Model

Wang

Rezaei

Tellambura

2020

IEEE Open J. Commun. Soc.

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Wireless powered communication networks (WPCNs) are commonly analyzed by using the linear energy harvesting (EH) model. However, since practical EH circuits are non-linear, the use of the linear EH model gives rise to distortions and mismatches. To overcome these issues, we propose a more realistic, nonlinear EH model. The model is based upon the error function and has three parameters. Their values are determined to best fit with measured data. We also develop the asymptotic version of this model. For comparative evaluations, we consider the linear and rational EH models. With these four EH models, we investigate the performance of a WPCN. It contains a multiple-antenna power station (PS), a signal-antenna wireless device (WD), and a multiple-antenna information receiving station (IRS). The WD harvests the energy broadcast by the PS in the PS-WD link, and then it uses the energy in the WD-IRS link to transfer information. We analyze the average throughput of delay-limited and delaytolerant transmission modes as well as the average bit error rate (BER) of binary phase-shift keying (BPSK) and binary differential phase-shift keying (BDPSK) over the four EH modes. As well, we derive the asymptotic expressions for the large PS antenna case and the effects of transmit power control. Furthermore, for the case of multiple WDs, we optimize energy beamforming and time allocation to maximize the minimum rate of the WDs. Finally, the performances of four EH models are validated by Monte-Carlo simulations.

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Section: Rational Modelmentioning

confidence: 84%

Section: B Energy Harvester Models and Resource Allocationsmentioning

confidence: 99%

Section: B Energy Harvester Models and Resource Allocationsmentioning

confidence: 99%

Section: B Energy Harvester Models and Resource Allocationsmentioning

confidence: 99%

Section: Energy Beamforming Optimizationmentioning

confidence: 99%

See 3 more Smart Citations

Performance Analysis and Resource Allocations for a WPCN With a New Nonlinear Energy Harvester Model

Wang

Rezaei

Tellambura

2020

IEEE Open J. Commun. Soc.

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Joint energy beamforming and bandwidth allocation for cooperative localization in passive sensor networks

Qu,

Zhao,

2024

Internet of Things

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Throughput Maximization for Wireless Powered Multimedia Communication Systems Under Statistical Latency Constraint

Yong-kang

Yang

2019

IEEE Access

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This paper investigates the relationship among the traffic throughput, statistical data latency requirement and system configurations in a wireless powered multimedia communication system. Firstly, a system model is built up with considerations of two operation modes and practical non-linear energy harvesting process. Based on the system model, the effective capacity of the considered system is derived based on the wireless charging parameter and fix data transmission rate. Then, the latency violation provability is studied by jointly taking effective capacity, traffic arrival and maximum tolerable data latency into account. Thereafter, the traffic maximization problem is transformed to the effective capacity maximization problem. Furthermore, We propose an optimal solution and a near-optimal solution to find out the system configurations of wireless charging time and transmission rate. Simulation results verify the accuracy of the near-optimal solution and also shed light on the operation mode selection in the considered system.

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Max-Min Fair Energy Beamforming for Wireless Powered Communication With Non-Linear Energy Harvesting

Cited by 13 publications

References 28 publications

Performance Analysis and Resource Allocations for a WPCN With a New Nonlinear Energy Harvester Model

Performance Analysis and Resource Allocations for a WPCN With a New Nonlinear Energy Harvester Model

Joint energy beamforming and bandwidth allocation for cooperative localization in passive sensor networks

Throughput Maximization for Wireless Powered Multimedia Communication Systems Under Statistical Latency Constraint

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