Goal-Oriented Semantic Information Transmission with Message-Sharing NOMA

Image transmission over wireless communications can be used in a variety of applications, such as smart city, surveillance systems, and Metaverse construction. Massive image transmission can indeed be a burden for wireless communication networks, especially in situations where a large number of users are trying to transmit high-resolution images simultaneously. An efficient image transmission framework in wireless communications is required to address the aforementioned challenge. In this article, we propose an image-transmission framework of goal-oriented semantic information transmission (SIT) with message-sharing (MS)-non-orthogonal multiple access (NOMA), in which only semantic information of interest is transmitted to each user. The framework includes five parts, namely, image transmission, image segmentation, object recognition, interest analysis, and semantic information transmission. During downlink transmission, MS-NOMA is adopted, which improves transmission efficiency by exploiting the existence of common messages among users in comparison to the conventional NOMA. We also design the quality of experience (QoE) to measure system performance. Finally, open research and challenges for the SIT with MS-NOMA are discussed.