Cluster-based wireless energy transfer for low complex energy receivers

Abeywickrama, Samith; Samarasinghe, Tharaka; Yuen, Chau; Zhang, Rui

doi:10.23919/wiopt.2018.8362859

Cited by 7 publications

(10 citation statements)

References 28 publications

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“…Satisfying the constraints will be comparatively easier as well when the two ERs are closer to each other, and hence, the infeasible region is expected to shrink when the number of ERs increases. An extension that stems on the idea presented in this paper on scheduling ERs that are closer to each other in terms of their channel phase can be found in [21].…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

Wireless energy transfer to a pair of energy receivers using signal strength feedback

Singhabahu

Samarasinghe

Abeywickrama

et al. 2018

2018 16th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)

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This paper focuses on wireless energy transfer (WET) to a pair of low complex energy receivers (ER), by only utilizing received signal strength indicator (RSSI) values that are fed back from the ERs to the energy transmitter (ET). Selecting the beamformer that maximizes the total average energy transfer between the ET and the ERs, while satisfying a minimum harvested energy criterion at each ER, is studied. This is a nonconvex constrained optimization problem which is difficult to solve analytically. Also, any analytical solution to the problem should only consists of parameters that the ET knows, or the ET can estimate, as utilizing only RSSI feedback values for channel estimation prohibits estimating some channel parameters. Thus, the paper focuses on obtaining a suboptimal solution analytically. It is proven that if the channels between the ET and the ERs satisfy a certain sufficient condition, this solution is in fact optimal. Simulations show that the optimality gap is negligibly small as well. Insights into a system with more than two ERs are also presented. To this end, it is highlighted that if the number of ERs is large enough, it is possible to always find a pair of ERs satisfying the sufficient condition, and hence, a pairwise scheduling policy that does not violate optimality can be used for the WET.

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Section: Simulation Results and Discussionmentioning

confidence: 99%

Wireless energy transfer to a pair of energy receivers using signal strength feedback

Singhabahu

Samarasinghe

Abeywickrama

et al. 2018

2018 16th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)

Self Cite

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“…The accuracy of the CSI estimation for WET has thus been investigated in [3], [16], [23][24][25][26][27][28].…”

Section: A Related Work and Motivationsmentioning

confidence: 99%

“…The authors optimize the size of the training codebook for channel acquisition to balance the trade-off between channel estimation precision and energy transmission time. These results are extended to multiple single-antenna energy receivers in [26]. Based on the feedback, the transmitter employs a maximum likelihood channel estimation method and clusters the receivers according to their channel phases during energy transmission.…”

Section: A Related Work and Motivationsmentioning

confidence: 99%

Wirelessly-powered Sensor Networks Power Allocation for Channel Estimation and Energy Beamforming

Du¹,

Ghadikolaei²,

Fischione

2020

Preprint

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Wirelessly-powered sensor networks (WPSNs) are becoming increasingly important in different monitoring applications. We consider a WPSN where a multiple-antenna base station, which is dedicated for energy transmission, sends pilot signals to estimate the channel state information and consequently shapes the energy beams toward the sensor nodes. Given a fixed energy budget at the base station, in this paper, we investigate the novel problem of optimally allocating the power for the channel estimation and for the energy transmission. We formulate this non-convex optimization problem for general channel estimation and beamforming schemes that satisfy some qualification conditions. We provide a new solution approach and a performance analysis in terms of optimality and complexity. We also present a closed-form solution for the case where the channels are estimated based on a least square channel estimation and a maximum ratio transmit beamforming scheme. The analysis and simulations indicate a significant gain in terms of the network sensing rate, compared to the fixed power allocation, and the importance of improving the channel estimation efficiency.

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“…Further, the efficacy of received signal strength indicator (RSSI) feedback values based CE protocols has been lately investigated in [19], [20]. However, these fully-digital EBF works [14]- [20] adopted an overly simplified linear rectification model for their investigation, which has been recently [21]- [26] shown to perform poorly for the practical RF EH circuits. The detailed investigation on RF EH performance using the statistical CSI as conducted in [25], [26] suggested that for an accurate characterization, a nonlinear EH model should be adopted during investigations.…”

Section: A State-of-the-artmentioning

confidence: 99%

“…InFig. 2, we plotted the linear model which is most commonly adopted due to its analytical simplicity[14]-[20]. Whereas, we have considered a more generic PWLA model[23] in place of CL (having L = 2) and CLC (i.e., L = 3) models.…”

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confidence: 99%

Optimal Channel Estimation for Hybrid Energy Beamforming Under Phase Shifter Impairments

Mishra

Johansson

2019

IEEE Trans. Commun.

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Smart multiantenna wireless power transmission can enable perpetual operation of energy harvesting (EH) nodes in the internet-of-things. Moreover, to overcome the increased hardware cost and space constraints associated with having large antenna arrays at the radio frequency (RF) energy source, the hybrid energy beamforming (EBF) architecture with single RF chain can be adopted. Using the recently proposed hybrid EBF architecture modeling the practical analog phase shifter impairments (API), we derive the optimal least-squares estimator for the energy source to EH user channel. Next, the average harvested power at the user is derived while considering the nonlinear RF EH model and a tight analytical approximation for it is also presented by exploring the practical limits on the API. Using these developments, the jointly global optimal transmit power and time allocation for channel estimation (CE) and EBF phases, that maximizes the average energy stored at the EH user is derived in closed form. Numerical results validate the proposed analysis and present nontrivial design insights on the impact of API and CE errors on the achievable EBF performance. It is shown that the optimized hybrid EBF protocol with joint resource allocation yields an average performance improvement of 37% over benchmark fixed allocation scheme.

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Cluster-based wireless energy transfer for low complex energy receivers

Cited by 7 publications

References 28 publications

Wireless energy transfer to a pair of energy receivers using signal strength feedback

Wireless energy transfer to a pair of energy receivers using signal strength feedback

Wirelessly-powered Sensor Networks Power Allocation for Channel Estimation and Energy Beamforming

Optimal Channel Estimation for Hybrid Energy Beamforming Under Phase Shifter Impairments

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