.png){kind=icon}
Return
Multiobjective Optimization for Intelligent Reflective Surface-Aided Physical-Layer Multicasting
.png){kind=icon}
OA
AI
DOI：10.1109/OJCOMS.2022.3156163.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
In this paper, we examine the use of intelligent reflective surface (IRS) to reconfigure the wireless propagation environment which assists the physical-layer multicast transmission with simple single-antenna radios in the network. Different phase-shift strategies are employed to adjust the reflection of the IRS. On the one hand, the max-min criterion is utilized to enhance the achievable rate of the receive nodes inside the multicast-target group. On the other hand, for the nodes outside the multicast-target group in the same network, we take advantage of another min-max criterion to let them all be less interfered with by the specific multicast communication. Multiobjective optimization is then set to reveal the compromises between the effect on the nodes of the two different groups. Simulation results show that the proposed IRS-aided physical-layer multicasting can fulfill the above-stated task, and can let the nodes in either group gain better results.
Keywords:
Multicast communication
Optimization
Wireless communication
Wireless sensor networks
Simulation
Tuning
Task analysis
Intelligent reflective surface (IRS)
physical-layer multicasting
max-min criterion
min-max criterion
convex optimization
semidefinite relaxation (SDR)
multiobjective optimization
Journal
I
IF:
4.3
Papers:
1.7K
Citations:
991
Organization
Cited Papers
.png){kind=icon}
ShareSaveShareSaveAnalysis and Optimization of an Intelligent Reflecting Surface-Assisted System With Interference
OAAI
OAAIShareSaveShareSaveShareSaveShareSave
View more