TY - GEN
T1 - Energy-Efficient Resource Allocation Design for Active IRS-Aided C-RSMA Systems
AU - Wang, Wenhao
AU - Yang, Lei
AU - Zhan, Yueying
AU - Qiao, Deli
AU - Kwan Ng, Derrick Wing
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - This paper investigates robust resource allocation design for active intelligent reflecting surface (IRS)-aided cog-nitive rate-splitting multiple access (C-RSMA) systems. In particular, an active IRS is deployed to shape a favorable wireless communication environment for enhancing the system performance. We aim to maximize the system energy efficiency by jointly optimizing the common rate allocations for the users, the transmit beamforming vectors at the coordinated base stations, and the active beamforming matrix at the IRS. We formulate the resource allocation design as a non-convex optimization problem taking into account the discrete nature of the IRS elements and the transmit power budget constraints of the base stations as well as the active IRS. To tackle the non-convex design problem, we propose a computationally effective iterative suboptimal algorithm. Simulation results reveal a nontrivial tradeoff between the system energy efficiency and the number of the IRS elements. Moreover, our results unveil that active IRS elements equipped with limited bit-resolution of discrete amplifiers and phase shifters is sufficient to achieve a significant gain in the system energy efficiency.
AB - This paper investigates robust resource allocation design for active intelligent reflecting surface (IRS)-aided cog-nitive rate-splitting multiple access (C-RSMA) systems. In particular, an active IRS is deployed to shape a favorable wireless communication environment for enhancing the system performance. We aim to maximize the system energy efficiency by jointly optimizing the common rate allocations for the users, the transmit beamforming vectors at the coordinated base stations, and the active beamforming matrix at the IRS. We formulate the resource allocation design as a non-convex optimization problem taking into account the discrete nature of the IRS elements and the transmit power budget constraints of the base stations as well as the active IRS. To tackle the non-convex design problem, we propose a computationally effective iterative suboptimal algorithm. Simulation results reveal a nontrivial tradeoff between the system energy efficiency and the number of the IRS elements. Moreover, our results unveil that active IRS elements equipped with limited bit-resolution of discrete amplifiers and phase shifters is sufficient to achieve a significant gain in the system energy efficiency.
UR - https://www.scopus.com/pages/publications/85198830468
U2 - 10.1109/WCNC57260.2024.10570954
DO - 10.1109/WCNC57260.2024.10570954
M3 - 会议稿件
AN - SCOPUS:85198830468
T3 - IEEE Wireless Communications and Networking Conference, WCNC
BT - 2024 IEEE Wireless Communications and Networking Conference, WCNC 2024 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 25th IEEE Wireless Communications and Networking Conference, WCNC 2024
Y2 - 21 April 2024 through 24 April 2024
ER -