🤖 AI Summary
This study addresses the resource bottlenecks of high-dimensional multimodal transmission in 6G immersive communications and the inability of conventional metrics to reflect physical information preservation quality. We propose an event-native immersive communication framework that defines communication objects via physical events, characterizes transceiver states using event beliefs, and introduces Event Belief Deficiency (EBD) as a novel Quality-of-Experience metric, overcoming the insensitivity of traditional NMSE to physical discrepancies. Leveraging Gaussian event belief modeling and mode-separable transmission techniques, simulations demonstrate that, compared to MSE-oriented schemes, the proposed approach reduces the normalized log-det EBD by up to 63.6% and decreases the required average received signal-to-noise ratio by 3.47 dB, thereby significantly enhancing semantic transmission efficiency.
📝 Abstract
The development of multimodal sensing capabilities is crucial for realizing immersive communications and enabling rich, natural remote interactions in future sixth-generation~(6G) communications. However, transmitting high-dimensional sensory streams places substantial pressure on wireless resources and leaves a fundamental question unresolved: what information about the underlying physical process should be preserved across wireless delivery? To address this issue, we establish an event-native immersive-communication framework in which a service-relevant physical event defines the communication object, while event beliefs represent the information available to transceiver agents before and after wireless delivery. Based on this event-native framework, we further propose event-belief deficiency (EBD) to evaluate quality of experience (QoE) in immersive communications, which differs from the conventional normalized mean-squared error (NMSE), as NMSE can be insensitive to physically distinct procedures whose stream distortions lie in a similar range. For Gaussian event beliefs with mode-separable delivery over Rayleigh fading, we derive the log-det EBD, its induced received signal-to-noise ratio (SNR) threshold, the exact outage probability, and the required transmit SNR. Simulation results with a physics-driven source show that stream NMSE can remain nearly unchanged across physically distinct event procedures, whereas log-det EBD reliably reflects their event-level uncertainty. Relative to a mean-squared-error (MSE)-oriented interface, event-native delivery reduces normalized log-det EBD by up to $63.6\%$ and lowers the required average received SNR by $3.47$~dB under the evaluated outage constraint, substantiating the effectiveness of the proposed framework.