Large-Scale Multi-Antenna Multi-Sine Wireless Power Transfer
File(s)
Accepted version
Author(s)
Huang, Y
Clerckx, B
Type
Journal Article
Abstract
Wireless Power Transfer (WPT) is expected to be a technology reshaping the landscape of low-power applications such as the Internet of Things, RF identification (RFID) networks, etc. To that end, multi-antenna multi-sine waveforms adaptive to the Channel State Information (CSI) have been shown to be a promising building block of WPT. However, the current design is computationally too complex to be applied to large-scale WPT, where the transmit signal is sent across a large number (tens) of antennas and frequencies. In this paper, we derive efficient singleuser and multi-user algorithms based on a generalizable optimization framework, in order to design transmit waveforms that maximize the weighted-sum/minimum rectenna DC output voltage. The study highlights the significant effect of the nonlinearity introduced by the rectification process on the design of waveforms in single/multi-user systems. Interestingly, in the single-user case, the optimal spatial domain beamforming, obtained prior to the frequency domain power allocation optimization, turns out to be Maximum Ratio Transmission (MRT). On the contrary, in the general multi-user weighted sum criterion maximization problem, the spatial domain beamforming optimization and the frequency domain power allocation optimization are coupled. Assuming channel hardening, low-complexity algorithms are proposed based on asymptotic analysis, to maximize the two criteria. The structure of the asymptotically optimal spatial domain precoder can be found prior to the optimization. The performance of the proposed algorithms is evaluated. Numerical results confirm the inefficiency of the linear model-based design for the single and multi-user scenarios. It is also shown that as nonlinear modelbased designs, the proposed algorithms can benefit from an increasing number of sinewaves at a computational cost much lower than the existing method. Simulation results highlight the significant benefits of the large-scale WPT architecture to boost the end-to-end power transfer efficiency and the transmission range.
Date Issued
2017-08-11
Date Acceptance
2017-07-28
Citation
IEEE Transactions on Signal Processing, 2017, 65 (21), pp.5812-5827
ISSN
1053-587X
Publisher
Institute of Electrical and Electronics Engineers
Start Page
5812
End Page
5827
Journal / Book Title
IEEE Transactions on Signal Processing
Volume
65
Issue
21
Copyright Statement
© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Subjects
Science & Technology
Technology
Engineering, Electrical & Electronic
Engineering
Wireless power transfer
energy harvesting
nonlinear model
massive MIMO
convex optimization
WAVE-FORM DESIGN
APPROXIMATION
OPTIMIZATION
EFFICIENCY
ALGORITHM
MD Multidisciplinary
Networking & Telecommunications
Publication Status
Published