Channel Estimation for Intelligent Reflecting Surface-Assisted Wireless Energy Transfer Network Using Only One-Bit Feedback.

Acquiring the wireless channel state information (CSI) is an essential task to reap the wireless system performance gain brought by intelligent reflecting surface (IRS). In this paper, we study an IRS-assisted wireless energy transfer (WET) network, where an energy receiver (ER) harvests the wireless energy transmitted from an energy transmitter (ET) with the help of an IRS. Different from the commonly adopted wireless CSI acquisition approaches such as pilot or codebook based methods, we propose a novel channel learning method that requires only one-bit feedback information from the ER. Specifically, each feedback bit indicates whether the increase or decrease of the harvested energy amount at the ER within the present interval as compared to the previous one. Based on the feedback information, the ET continually adjusts its transmit beamforming in subsequent channel learning intervals to help infer the cascaded ET-IRS-ER CSI. It is worth noting that an optimization technique named analytic center cutting plane method (ACCPM) is applied in the channel learning phase. Numerical results unveil that our proposed one-bit feedback based channel estimation method is able to effectively estimate the cascaded ET-IRS-ER channel, and greatly reduce the requirement on the hardware complexity of the ER simultaneously.