Energy Beamforming with One-Bit Feedback (1312.1444v3)

Abstract: Wireless energy transfer (WET) has attracted significant attention recently for providing energy supplies wirelessly to electrical devices without the need of wires or cables. Among different types of WET techniques, the radio frequency (RF) signal enabled far-field WET is most practically appealing to power energy constrained wireless networks in a broadcast manner. To overcome the significant path loss over wireless channels, multi-antenna or multiple-input multiple-output (MIMO) techniques have been proposed to enhance the transmission efficiency and distance for RF-based WET. However, in order to reap the large energy beamforming gain in MIMO WET, acquiring the channel state information (CSI) at the energy transmitter (ET) is an essential task. This task is particularly challenging for WET systems, since existing channel training and feedback methods used for communication receivers may not be implementable at the energy receiver (ER) due to its hardware limitation. To tackle this problem, in this paper we consider a multiuser MIMO system for WET, where a multiple-antenna ET broadcasts wireless energy to a group of multiple-antenna ERs concurrently via transmit energy beamforming. By taking into account the practical energy harvesting circuits at the ER, we propose a new channel learning method that requires only one feedback bit from each ER to the ET per feedback interval. The feedback bit indicates the increase or decrease of the harvested energy by each ER between the present and previous intervals, which can be measured without changing the existing hardware at the ER. Based on such feedback information, the ET adjusts transmit beamforming in different training intervals and at the same time obtains improved estimates of the MIMO channels to ERs by applying a new approach termed analytic center cutting plane method (ACCPM).

• The paper proposes an innovative one-bit feedback channel learning technique using the Analytic Center Cutting Plane Method (ACCPM) to optimize energy beamforming for wireless energy transfer (WET) in multi-user scenarios, circumventing complex traditional CSI procedures.
• The ACCPM-based algorithm uses a single feedback bit per receiver per interval to dynamically adjust beamforming, demonstrating significant improvements in energy transfer efficiency and convergence speed over competing one-bit feedback schemes, particularly as the number of energy receivers increases.
• This research advances understanding of low-complexity feedback in MIMO systems and supports the development of sustainable power solutions for energy-constrained devices in distributed networks like sensor systems and IoT applications.

Energy Beamforming with One-Bit Feedback: An Overview

Wireless energy transfer (WET) is a promising technology for powering energy-constrained devices without direct physical connections. The utilization of radio frequency (RF) signals in far-field WET has sparked interest given its potential applicability to various scenarios, such as sensor networks. The efficiency of RF-based WET, especially over long distances, stands to benefit substantially from multi-antenna or multiple-input multiple-output (MIMO) techniques. These technologies, by leveraging spatial diversity through beamforming, can considerably enhance transmission efficiency and range. However, acquiring accurate channel state information (CSI) remains challenging, especially considering the hardware limitations inherent in devices designed primarily as energy receivers (ERs).

The paper by Xu and Zhang proposes an innovative solution through a channel learning technique with minimal feedback requirements—a single bit per feedback interval per ER. The method circumvents the complexities of traditional channel training and feedback procedures, which are often infeasible for energy-centric devices. Each feedback bit is leveraged to adjust energy beamforming dynamically, optimizing the power received by ERs and improving the CSI estimates for subsequent intervals. This process employs the unique analytic center cutting plane method (ACCPM), which is essential in convex optimization to facilitate the channel estimation task.

A distinctive aspect of the approach is its focus on multiuser scenarios, where the transmitter (ET) serves multiple ERs simultaneously. The ACCPM-based algorithm adapts quickly without sacrificing convergence speed despite estimating multiple MIMO channels concurrently. Simulation results presented in the paper demonstrate significant improvements in both energy transfer efficiency and convergence speed over competing one-bit feedback schemes. These outcomes are particularly pronounced as the number of ERs increases, showcasing the algorithm’s scalability and operational robustness in dense network environments.

The implications of this work span both theoretical and practical domains. Theoretically, the paper advances understanding of low-complexity feedback mechanisms in MIMO systems, potentially impacting future designs in both WET and traditional communication infrastructure. Practically, the research supports the development of sustainable power solutions in communication networks, notably beneficial in distributed sensor systems and IoT applications that require constant energy replenishment.

Future explorations may investigate leveraging more than one feedback bit per interval, further enhancing estimation accuracy and transmission efficiency. Additionally, extending ACCPM concepts to broader wireless communication contexts can reveal potential performance gains in channel learning and feedback processes, fostering continued innovation in both academia and industry. The creativity and foresight inherent in proposing such minimalistic, yet highly effective, feedback strategies signal a pivotal step towards optimized and sustainable WET systems.