AAMS: Application-Aware MCS Selection With Mode Switching for QoE-Driven Large-Scale Media Transmission in 6G Mobile Networks - Park, Somin; Choi, Minji; Ahn, Jin-Hyun; Ho Kim, Dong; You, Cheolwoo (IEEE access, 2025)
Large-scale media data, such as 3D point cloud videos, have received increasing attention as a key content type for 6G mobile communication services. When delivering large-scale media in real time, it is necessary to transmit high-resolution data to meet the high demands of users. However, frequent retransmissions due to transmission errors may cause various issues across the entire system. Ultra-low latency and ultra-high-speed transmission are critical factors that guarantee high Quality of Experience (QoE) in real-time, large-scale media transmission systems. However, conventional modulation and coding scheme (MCS) selection approaches, which primarily focus on maximizing cell throughput, operate based on a fixed target block error rate without considering user content characteristics or usage environments. Consequently, these approaches face limitations in supporting a wide range of future services with diverse QoE requirements. This study proposes a novel MCS selection scheme that not only considers cell throughput maximization but also ensures retransmission stability for real-time, large-scale media data transmission. The proposed scheme adaptively adjusts the MCS selection thresholds based on user network conditions and feedback information associated with each MCS level. In addition, by enabling the selection of only the essential MCS levels needed for service provision, it maximizes the transmission efficiency while enhancing the reliability of real-time, large-scale media data transmission. Moreover, to address diverse QoE requirements, the proposed scheme is further enhanced through the introduction of a mode-switching mechanism for MCS selection based on service types and user mobility. Finally, the simulation results based on 3D point cloud video transmission demonstrate that the proposed scheme effectively mitigates retransmission issues in large-scale data services with high resolution, thereby enhancing user QoE.