Time-Division Energy Beamforming for Multiuser Wireless Power Transfer With Non-Linear Energy Harvesting

Ma, Ganggang; Xu, Jie; Liu, Ya-Feng; Moghadam, Mohammad R. Vedady

doi:10.1109/lwc.2020.3020324

Cited by 18 publications

(11 citation statements)

References 21 publications

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“…one energy beam with adjustable weights over time achieves the same optimal performance as conventional multi-beam design. A similar phenomenon has also been revealed in [9] under non-linear energy harvesting (EH) model. Recall that IRS is only implemented with a single set of coefficients, which, however, is not capable of providing the optimal socalled multi-beam transmission in WET.…”

Section: Introductionsupporting

confidence: 67%

“…On the other hand, in multiuser WET system, how to fairly enhance energy transmission efficiency is also an important issue, which has been studied in prior works [8], [9]. It was shown in [8] that the multi-beam energy transmission is the optimal design for the multi-antenna energy transmitter (ET) to maximize the minimum energy harvested by all the energy receivers (ERs).…”

Section: Introductionmentioning

confidence: 99%

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Achieving Multi-beam Gain in Intelligent Reflecting Surface Assisted Wireless Energy Transfer

Chi¹,

Wu²,

Meng³

et al. 2022

Preprint

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Section: Introductionsupporting

confidence: 67%

Section: Introductionmentioning

confidence: 99%

Achieving Multi-beam Gain in Intelligent Reflecting Surface Assisted Wireless Energy Transfer

Chi¹,

Wu²,

Meng³

et al. 2022

Preprint

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“…Previous Works. Our proposed RaJ scheme differs [7,[10][11][12][13][14][15][16][17][18][19][20][21][22] which investigated problems of security and/or reliability for the NL-EH (References which studied the L-EH with/without relaying (e.g., [5,6,9]) or the NL-EH without relaying (e.g., [23][24][25][26][27][28][29][30][31][32][33][34][35]) must not be surveyed because this paper considers simultaneously the NL-EH, relaying, and jamming.) with relaying.…”

Section: Introductionmentioning

confidence: 99%

Relay Selection‐and‐Jamming Scheme with Nonlinear Energy Harvesting

Pham-MinhTriet

Ho-Van

Nguyen

et al. 2021

Wireless Communications and Mobile Computing

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When direct source-destination communications are in outage, relay selection is a preferable solution to improve reliability for this communications. However, such a relay selection makes the eavesdropper better overhear source data through both source-relay and relay-destination communication hops, losing data security. To improve both reliability and security, this paper proposes a relay selection-and-jamming (RaJ) scheme to select one intermediate node as a conventional relay and another node as a jammer. To enhance energy efficiency, all intermediate nodes harvest radio frequency energy in source signals for their operations with nonlinear energy harvesting (NL-EH). The security and reliability of the RaJ scheme are assessed through suggested rigorous/asymptotic expressions and are significantly better than two benchmark schemes without neither jamming nor both relay selection and jamming. Additionally, they can be optimized with reasonable selection of specifications. Moreover, the NL property of the energy harvesters dramatically affects the reliability but negligibly degrades the security for the RaJ scheme. Furthermore, the linear EH (L-EH) is more reliable but less secure than the NL-EH.

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“…Under WPCN and wireless powered MEC applications, the near-far issue may become even more severe, in which the far-apart devices with less harvested energy need to consume more energy for information transmission to meet the same quality of service (QoS) as nearby devices. To tackle these challenges, there have been prior works that proposed various techniques to enhance the energy transfer efficiency via, e.g., transmit energy beamforming [5], [8], [24]- [27], energy waveform optimization [28], [29], adaptive power control [30], and deployment optimization [31] for the ETs. Despite these research progresses, the ultra-dense deployment of ETs at fixed locations is in general necessary to achieve ubiquitous coverage for WPT.…”

Section: Introductionmentioning

confidence: 99%

UAV-Enabled Wireless Power Transfer: A Tutorial Overview

Xie

Cao

et al. 2021

Preprint

Self Cite

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Unmanned aerial vehicle (UAV)-enabled wireless power transfer (WPT) has recently emerged as a promising technique to provide sustainable energy supply for widely distributed low-power ground devices (GDs) in large-scale wireless networks. Compared with the energy transmitters (ETs) in conventional WPT systems which are deployed at fixed locations, UAV-mounted aerial ETs can fly flexibly in the three-dimensional (3D) space to charge nearby GDs more efficiently. This paper provides a tutorial overview on UAV-enabled WPT and its appealing applications, in particular focusing on how to exploit UAVs' controllable mobility via their 3D trajectory design to maximize the amounts of energy transferred to all GDs in a wireless network with fairness. First, we consider the single-UAV-enabled WPT scenario with one UAV wirelessly charging multiple GDs at known locations. To solve the energy maximization problem in this case, we present a general trajectory design framework consisting of three innovative approaches to optimize the UAV trajectory, which are multi-location hovering, successive-hover-andfly, and time-quantization-based optimization, respectively. Next, we consider the multi-UAV-enabled WPT scenario where multiple UAVs cooperatively charge many GDs in a large area. Building upon the single-UAV trajectory design, we propose two efficient schemes to jointly optimize multiple UAVs' trajectories, based on the principles of UAV swarming and GD clustering, respectively. Furthermore, we consider two important extensions of UAV-enabled WPT, namely UAV-enabled wireless powered L. Xie and X. Cao are with the

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Time-Division Energy Beamforming for Multiuser Wireless Power Transfer With Non-Linear Energy Harvesting

Cited by 18 publications

References 21 publications

Achieving Multi-beam Gain in Intelligent Reflecting Surface Assisted Wireless Energy Transfer

Achieving Multi-beam Gain in Intelligent Reflecting Surface Assisted Wireless Energy Transfer

Relay Selection‐and‐Jamming Scheme with Nonlinear Energy Harvesting

UAV-Enabled Wireless Power Transfer: A Tutorial Overview

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