期刊
IEEE ACCESS
卷 5, 期 -, 页码 1743-1752出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2017.2666299
关键词
Wireless power transfer; radio-frequency energy harvesting; software-defined radios; experiments; beamforming
资金
- Verizon through NYC Media Laboratory
- Peacock Program of Shenzhen [KQTD2015071715073798]
- Leading Talents Program of Guangdong Province [00201510]
Wireless power transfer (WPT) has long been one of the main goals of Nikola Tesla, the forefather of electromagnetic applications. In this paper, we investigate radio-frequency (RF) beamforming in the radiative far field for WPT. First, an analytical model of the channel fading is presented, and a blind adaptive beamforming algorithm is adapted to the wireless power transfer context. The algorithm is computationally light, because we need not explicitly estimate the channel state information. A testbed with a multiple-antenna software-defined radio configuration on the transmitting side and a programmable energy harvester on the receiving side is then developed to validate the algorithm in this specific power application. From the results, it can be seen that the implementation of this version of beamforming indeed improves the harvested power. Specifically, at various distances from 50 cm to 1.5 m, the algorithm converges with two, three and four antennas with an increasing gain as we increase the number of antennas. These encouraging results could have far-reaching consequences in providing wireless power to Internet of Things (IoT) devices, our target application.
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