1.
Yan, Hua; Chen, Yunfei
Optimum Distance for In-Flight UAV-to-UAV Wireless Charging Journal Article
In: IEEE Access, vol. 13, pp. 143914–143924, 2025, ISSN: 2169-3536.
Abstract | Links | BibTeX | Tags: Aperture antennas, Autonomous aerial vehicles, Batteries, Energy Efficiency, Energy loss, far-field, Inductive charging, near-field, Receiving antennas, RF signals, Simultaneous wireless information and power transfer, Transmitting antennas, UAV communications, Wireless communication, Wireless communications, wireless power transfer (WPT)
@article{yan_optimum_2025,
title = {Optimum Distance for In-Flight UAV-to-UAV Wireless Charging},
author = {Hua Yan and Yunfei Chen},
url = {https://ieeexplore.ieee.org/document/11123803/},
doi = {10.1109/ACCESS.2025.3598733},
issn = {2169-3536},
year = {2025},
date = {2025-01-01},
urldate = {2025-10-08},
journal = {IEEE Access},
volume = {13},
pages = {143914–143924},
abstract = {Wireless charging is a promising technology for communications using battery-powered unmanned aerial vehicles (UAVs). In this paper, the optimal distance for UAV-to-UAV in-flight wireless charging and communications is studied. Considering the practical applications, two schemes are proposed. In the first scheme, the discharging UAV (D-UAV) and the charged UAV (C-UAV) are aligned during charging, which requires the D-UAV and the C-UAV to remain relatively stationary. In the second scheme, the D-UAV and the C-UAV move during charging. For both schemes, we aim to maximize the received energy at the C-UAV under the condition that the minimum achievable rate for communications is met. Numerical results show that the optimal distance exists in the Fresnel zone. They also show that the optimal distance increases with the charging frequency. This work provides useful guidance for UAV in-flight wireless charging and communications system designs.},
keywords = {Aperture antennas, Autonomous aerial vehicles, Batteries, Energy Efficiency, Energy loss, far-field, Inductive charging, near-field, Receiving antennas, RF signals, Simultaneous wireless information and power transfer, Transmitting antennas, UAV communications, Wireless communication, Wireless communications, wireless power transfer (WPT)},
pubstate = {published},
tppubtype = {article}
}
Wireless charging is a promising technology for communications using battery-powered unmanned aerial vehicles (UAVs). In this paper, the optimal distance for UAV-to-UAV in-flight wireless charging and communications is studied. Considering the practical applications, two schemes are proposed. In the first scheme, the discharging UAV (D-UAV) and the charged UAV (C-UAV) are aligned during charging, which requires the D-UAV and the C-UAV to remain relatively stationary. In the second scheme, the D-UAV and the C-UAV move during charging. For both schemes, we aim to maximize the received energy at the C-UAV under the condition that the minimum achievable rate for communications is met. Numerical results show that the optimal distance exists in the Fresnel zone. They also show that the optimal distance increases with the charging frequency. This work provides useful guidance for UAV in-flight wireless charging and communications system designs.
2.
Lu, Zhizheng; Han, Yu; Jin, Shi; Matthaiou, Michail
Near-Field Localization and Channel Reconstruction for ELAA Systems Journal Article
In: IEEE Transactions on Wireless Communications, vol. 23, no. 7, pp. 6938–6953, 2024, ISSN: 1558-2248.
Abstract | Links | BibTeX | Tags: Antenna arrays, Channel estimation, Channel reconstruction, localization, Location awareness, Mobile antennas, near-field, PEB, Precoding, Radio frequency, Receiving antennas, subarray hybrid ELAA systems
@article{lu_near-field_2024,
title = {Near-Field Localization and Channel Reconstruction for ELAA Systems},
author = {Zhizheng Lu and Yu Han and Shi Jin and Michail Matthaiou},
url = {https://ieeexplore.ieee.org/document/10345492},
doi = {10.1109/TWC.2023.3336328},
issn = {1558-2248},
year = {2024},
date = {2024-07-01},
urldate = {2025-10-08},
journal = {IEEE Transactions on Wireless Communications},
volume = {23},
number = {7},
pages = {6938–6953},
abstract = {In this paper, an efficient near-field channel reconstruction and user equipment (UE) localization scheme is proposed for extremely large antenna array (ELAA) systems using a subarray hybrid precoding architecture. Considering the non-negligible signal amplitude and phase variations across the different receive antennas, a more realistic channel model is adopted. The channel environment, with an approximate smooth ground surface, is modeled. In fact, the channel can be divided into a line-of-sight (LoS) path, a reflection path and some non-LoS (NLoS) paths. Based on the sparsity of the channel in the spatial domain, the damped Newtonized orthogonal matching pursuit (DNOMP) algorithm is also proposed to accurately estimate the multipaths, and reconstruct the channel. Then, a UE localization algorithm is proposed, which can detect the existence of the LoS path and locate the UE. A joint localization algorithm is also devised to further increase the positioning reliability. Simulation results verify that the DNOMP algorithm can reconstruct the channel with better NMSE performance than other schemes. The localization algorithm can locate the UE with low error whenever the LoS path exists or not, with an accuracy close enough to the position error bound (PEB), while the joint localization algorithm can further enhance the positioning reliability.},
keywords = {Antenna arrays, Channel estimation, Channel reconstruction, localization, Location awareness, Mobile antennas, near-field, PEB, Precoding, Radio frequency, Receiving antennas, subarray hybrid ELAA systems},
pubstate = {published},
tppubtype = {article}
}
In this paper, an efficient near-field channel reconstruction and user equipment (UE) localization scheme is proposed for extremely large antenna array (ELAA) systems using a subarray hybrid precoding architecture. Considering the non-negligible signal amplitude and phase variations across the different receive antennas, a more realistic channel model is adopted. The channel environment, with an approximate smooth ground surface, is modeled. In fact, the channel can be divided into a line-of-sight (LoS) path, a reflection path and some non-LoS (NLoS) paths. Based on the sparsity of the channel in the spatial domain, the damped Newtonized orthogonal matching pursuit (DNOMP) algorithm is also proposed to accurately estimate the multipaths, and reconstruct the channel. Then, a UE localization algorithm is proposed, which can detect the existence of the LoS path and locate the UE. A joint localization algorithm is also devised to further increase the positioning reliability. Simulation results verify that the DNOMP algorithm can reconstruct the channel with better NMSE performance than other schemes. The localization algorithm can locate the UE with low error whenever the LoS path exists or not, with an accuracy close enough to the position error bound (PEB), while the joint localization algorithm can further enhance the positioning reliability.