Geometric Dynamics and Semantic Communication for Retinal-Resolution XR Video Transmission: A Technical and Systems-Level Analysis

This work presents a systems-level analysis of retinal-resolution Extended Reality (XR) video transmission, reframing the problem away from traditional compression efficiency and toward geometric capacity allocation under strict causal constraints. Instead of treating XR bandwidth limitations as a rate–distortion optimization issue, the paper analyzes how spatial representation, perceptual heterogeneity, and latency budgets jointly determine what is feasible in real-time XR systems. The study introduces a conceptual separation between signal-level representation (pixel grids and sampling geometry) and semantic-level structure (hierarchical scene organization), arguing that conflating these layers leads to incorrect assumptions about achievable bandwidth reduction. Within this framework, XR transmission is examined as a problem of controlled distortion distribution across perceptually distinct regions, rather than uniform fidelity across the visual field. A key emphasis is placed on Motion-to-Photon (MTP) latency as a first-class causal constraint derived from human physiology. The analysis demonstrates that decoder-side reconstruction latency, rather than network throughput, is the dominant bottleneck for advanced semantic or generative approaches under real-time interaction requirements. Experimental results at an abstract level show that spatially adaptive geometric preprocessing can significantly alter the distribution of reconstruction error in favor of perceptually important regions, while also highlighting scenarios where such strategies fail. These findings support the broader conclusion that many proposed semantic and generative XR communication architectures are theoretically appealing but practically blocked by current hardware constraints. Overall, the paper contributes a reframing of the XR bandwidth problem as a geometric–causal systems challenge, providing negative results, boundary conditions, and architectural implications that are relevant for future XR platforms, edge computing, and next-generation wireless systems.