TY - GEN
T1 - Multi-Functional Reconfigurable Intelligent Surface
AU - Wang, Wen
AU - Ni, Wanli
AU - Tian, Hui
AU - Eldar, Yonina C.
N1 - Publisher Copyright: © 2023 IEEE.
PY - 2023/6/4
Y1 - 2023/6/4
N2 - In this paper, we propose a new multi-functional reconfigurable intelligent surface (MF-RIS) architecture. Different from conventional RIS that only reflects signals, MF-RIS supports multiple functionalities on one surface, including reflection, transmission, amplification, and energy harvesting. As such, MF-RIS is capable of overcoming the double-fading attenuation and achieving full-space coverage by harvesting energy from the base station (BS). The physical implementation and the signal model of MF-RIS are introduced from the perspective of wireless communications. Then, we formulate a sum rate (SR) maximization problem in an MF-RIS-aided non-orthogonal multiple access network. By jointly optimizing the transmit strategy of the BS and the coefficient of the MF-RIS, we design an iterative algorithm to solve the formulated non-convex problem efficiently. Simulation results show that: i) MF-RIS provides up to 98.8% higher SR gain than self-sustainable RIS. ii) There exists a non-trivial trade-off between throughput improvement and self-sustainability, due to the limited number of RIS elements.
AB - In this paper, we propose a new multi-functional reconfigurable intelligent surface (MF-RIS) architecture. Different from conventional RIS that only reflects signals, MF-RIS supports multiple functionalities on one surface, including reflection, transmission, amplification, and energy harvesting. As such, MF-RIS is capable of overcoming the double-fading attenuation and achieving full-space coverage by harvesting energy from the base station (BS). The physical implementation and the signal model of MF-RIS are introduced from the perspective of wireless communications. Then, we formulate a sum rate (SR) maximization problem in an MF-RIS-aided non-orthogonal multiple access network. By jointly optimizing the transmit strategy of the BS and the coefficient of the MF-RIS, we design an iterative algorithm to solve the formulated non-convex problem efficiently. Simulation results show that: i) MF-RIS provides up to 98.8% higher SR gain than self-sustainable RIS. ii) There exists a non-trivial trade-off between throughput improvement and self-sustainability, due to the limited number of RIS elements.
KW - Multi-functional RIS
KW - energy harvesting
KW - implementation design
KW - throughput maximization
UR - https://www.scopus.com/pages/publications/86000381852
U2 - 10.1109/ICASSP49357.2023.10096886
DO - 10.1109/ICASSP49357.2023.10096886
M3 - Conference contribution
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
BT - ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing, Proceedings
T2 - 48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023
Y2 - 4 June 2023 through 10 June 2023
ER -