Resource Allocation and Common Message Selection for Task-Oriented Semantic Information Transmission with RSMA

Abstract

Image transmission over wireless communications can be used in a variety of applications, such as smart cities, surveillance systems, and Metaverse construction. In this paper, we propose a task-oriented semantic information transmission (SIT) framework with rate-splitting multiple access (RSMA) for image transmission. As such, only the semantic information of interest is transmitted to each user, and RSMA is adopted to improve transmission efficiency. We also design the quality of experience (QoE) for the framework as a performance metric, which can be used for transmission-parameter optimization. Specifically, we first optimize power allocation with the top-N common message selection strategy. To further improve system performance, we jointly optimize power allocation and common message selection. Simulation results show that the proposed task-oriented SIT framework with RSMA outperforms the space-division multiple access (SDMA)-based benchmark, which reflects the effectiveness of the proposed framework. Furthermore, the results show that optimizing power allocation can improve performance significantly as compared with fixing power allocation, and the joint optimization of power allocation and common message selection has an obvious performance gain over optimizing only power allocation, which demonstrates the effectiveness of the designed optimization algorithms.