@inproceedings{b71031d7d4624a40b4bcdf916d4e7307,
title = "Self-Sustainable Intelligent Omni-Surface Aided Multi-User Wireless Networks",
abstract = "We investigate a new self-sustainable intelligent omni-surface (S-IOS) aided multi-user wireless network, where the S-IOS harvests the radio frequency energy from the signals transmitted by the access point (AP) and exploits the harvested energy to provide full-dimensional beamforming services for the users. We design a joint optimization problem of transmit beamforming at the AP, refraction/reflection beamforming at the S-IOS, and energy harvesting schedule at the S-IOS, to maximize the sum rate of the overall network. A computationally-efficient algorithm is developed to solve the problem. Numerical results demonstrate the significant importance of the S-IOS for spectral and energy efficient wireless communications.",
author = "Hao Luo and Lu Lv and Long Yang and Qingqing Wu and Zhiguo Ding and Naofal Al-Dhahir and Jian Chen",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 98th IEEE Vehicular Technology Conference, VTC 2023-Fall ; Conference date: 10-10-2023 Through 13-10-2023",
year = "2023",
doi = "10.1109/VTC2023-Fall60731.2023.10333508",
language = "British English",
series = "IEEE Vehicular Technology Conference",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2023 IEEE 98th Vehicular Technology Conference, VTC 2023-Fall - Proceedings",
address = "United States",
}