[Paper Review] Prototyping and Experimentation of a Closed-Loop Wireless Power Transmission with Channel Acquisition and Waveform Optimization

Jung-Hoon Kim, Bruno Clerckx+1 more|arXiv (Cornell University)|Apr 6, 2017

Energy Harvesting in Wireless Networks3 references3 citations

TL;DR

This paper presents the first experimental prototype of a closed-loop wireless power transfer system with real-time channel acquisition and adaptive waveform optimization using a software-defined radio (SDR) platform and a custom voltage-doubler rectenna. By dynamically adjusting the amplitude and phase of eight multisine tones based on estimated channel state information via the scaled matched filter (SMF) method, the system achieves 9.8% to 36.8% higher average harvested DC power compared to non-adaptive waveforms in real-world office environments, especially in frequency-selective (NLoS) conditions.

ABSTRACT

A systematic design of adaptive waveform for Wireless Power Transfer (WPT) has recently been proposed and shown through simulations to lead to significant performance benefits compared to traditional non-adaptive and heuristic waveforms. In this study, we design the first prototype of a closed-loop wireless power transfer system with adaptive waveform optimization based on Channel State Information acquisition. The prototype consists of three important blocks, namely the channel estimator, the waveform optimizer, and the energy harvester. Software Defined Radio (SDR) prototyping tools are used to implement a wireless power transmitter and a channel estimator, and a voltage doubler rectenna is designed to work as an energy harvester. A channel adaptive waveform with 8 sinewaves is shown through experiments to improve the average harvested DC power at the rectenna output by 9.8% to 36.8% over a non-adaptive design with the same number of sinewaves.

Motivation & Objective

• To demonstrate the first real-world prototype of a closed-loop wireless power transfer system with dynamic channel acquisition and waveform optimization.
• To validate the theoretical performance gains of channel-adaptive waveforms over non-adaptive and heuristic designs in practical, over-the-air environments.
• To evaluate the impact of frequency selectivity (e.g., NLoS) on the effectiveness of adaptive waveform design in real-world WPT systems.
• To assess the feasibility and performance of low-complexity waveform optimization using the scaled matched filter (SMF) method in a real-time SDR-based system.

Proposed method

• The system architecture integrates a channel estimator, a waveform optimizer, and an energy harvester using SDR-based hardware and LabVIEW software.
• Channel state information (CSI) is acquired via pilot tones using least-squares estimation over a 10 MHz bandwidth with 20 symbols (320 μs) dedicated to training.
• The waveform optimizer uses the scaled matched filter (SMF) method to compute amplitude and phase parameters for eight uniformly spaced sinewaves based on the estimated CSI.
• The transmitter modulates and transmits the optimized multisine waveform using an SDR platform (USRP N210) at 2.4 GHz center frequency.
• A custom voltage-doubler rectenna using a Skyworks SMS7630 Schottky diode is designed and matched to 50 Ω, with an input return loss of -30 dB at 2.4 GHz.
• The system operates under a fixed transmit power of 35 dBm, and harvested DC power is measured over two-minute intervals in static office conditions.

Experimental results

Research questions

• RQ1 Can a closed-loop WPT system with real-time channel acquisition and adaptive waveform optimization achieve measurable performance gains over non-adaptive designs in real-world environments?
• RQ2 How does the performance gain of adaptive waveforms vary between line-of-sight (LoS) and non-line-of-sight (NLoS) propagation conditions?
• RQ3 To what extent does the scaled matched filter (SMF) method enable low-complexity, practical implementation of channel-adaptive waveforms in a real-time SDR platform?
• RQ4 What is the measurable improvement in harvested DC power when using CSI-based waveform optimization compared to uniform power allocation across sinewaves?

Key findings

• The use of channel-adaptive waveforms based on CSI estimation increased average harvested DC power by 9.8% in a line-of-sight (LoS) environment.
• In a non-line-of-sight (NLoS) environment with higher frequency selectivity, the performance gain reached 36.8% over non-adaptive waveforms.
• The system achieved a 25.9% improvement in harvested DC power in a second NLoS test case, confirming the benefit of adaptation in frequency-selective channels.
• The rectenna achieved 12% RF-to-DC conversion efficiency at -20 dBm input power for a continuous wave signal, validating the energy harvester's effectiveness.
• The results confirm that waveform optimization based on CSI yields significantly higher end-to-end power transfer efficiency than non-adaptive or heuristic designs, especially in frequency-selective fading environments.
• The prototype demonstrates the feasibility and real-world benefits of closed-loop WPT with dynamic channel acquisition and low-complexity waveform optimization using SDR and practical hardware components.