Massive Wireless Energy Transfer Without Channel State Information via Imperfect Intelligent Reflecting Surfaces

• Published in: IEEE transactions on vehicular technology Vol. 73; no. 6; pp. 8529 - 8541
• Main Authors: Luo, Cheng, Hu, Jie, Xiang, Luping, Yang, Kun, Wong, Kai-Kit
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.06.2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: 6G mobile communication; Channel estimation; Channel state information-free; Communication system security; Hardware; imperfect hardware; intelligent reflecting surface; Internet of Things; massive energy receivers; Receivers; Reconfigurable intelligent surfaces; Wireless communication; wireless energy transfer
• ISSN: 0018-9545; 1939-9359
• DOI: 10.1109/TVT.2024.3361210

Intelligent Reflecting Surface (IRS) utilizes low-cost, passive reflecting elements to enhance the passive beam gain, improve Wireless Energy Transfer (WET) efficiency, and enable its deployment for numerous Internet of Things (IoT) devices. However, the increasing number of IRS elements presents considerable channel estimation challenges. This is due to the lack of active Radio Frequency (RF) chains in an IRS, while pilot overhead becomes intolerable. To address this issue, we propose a Channel State Information (CSI)-free scheme that maximizes received energy in a specific direction and covers the entire space through phased beam rotation. Furthermore, we take into account the impact of an imperfect IRS and meticulously design the active precoder and IRS reflecting phase shift to mitigate its effects. Our proposed technique does not alter the existing IRS hardware architecture, allowing for easy implementation in the current system, and enabling access or removal of any Energy Receivers (ERs) without additional cost. Numerical results illustrate the efficacy of our CSI-free scheme in facilitating large-scale IRS without compromising performance due to excessive pilot overhead. Furthermore, our scheme outperforms the CSI-based counterpart in scenarios involving large-scale ERs, making it a promising solution in the era of IoT.