Tube-Structured Incremental Semantic HARQ for Generative Video Receivers
2026-05-11 • Multimedia
Multimedia
AI summaryⓘ
The authors study how to better fix video data when some information is lost during transmission, which is important for delivering videos over limited networks. Instead of sending or resending fixed blocks of data, they suggest sending smaller, time-focused chunks called 'tube-structured packages' that make it easier to recover the video smoothly over time. Their method improves how quickly video quality stabilizes after errors, especially in tougher network conditions, though the final video quality ends up similar to older methods. This approach shows that deciding how to ask for resending data is an important part of the system design.
Generative semantic communicationVideo reconstructionHybrid Automatic Repeat Request (HARQ)Retransmission unitsTube-structured packagesRecovery trajectoryBandwidth-limited multimediaTemporal correlationAoIS-AUC objective
Authors
Xuesong Wang, Xinyan Xie, Runxin Zhang
Abstract
Generative semantic communication uses receiver-side generative priors to reconstruct visual content from compact semantics, making it attractive for bandwidth-limited multimedia delivery. For video, reliable recovery remains difficult because errors accumulate over time, useful evidence is temporally correlated, and the receiver must make decisions under limited interaction, retransmission, and reconstruction budgets. Existing generative semantic communication studies mainly emphasize representation, compression, or generative reconstruction, while recent error-resilient and semantic-HARQ methods still largely operate on encoder-defined or frame-block retransmission units. This paper studies receiver-driven semantic HARQ for generative video reconstruction under a budget-constrained AoIS-AUC objective and argues that the retransmission primitive is itself an important system design variable. We propose tube-structured package-native requests, in which temporally local packages are the channel-visible HARQ objects and are transmitted, dropped, received, and committed at package granularity. Under a controlled comparison protocol with matched backbone, budgets, and channel model, this primitive yields lower time-weighted recovery cost than competitive block-based baselines in practically relevant moderate-to-harsh regimes, while the gap naturally shrinks in near-clean channels. The gain mainly appears as earlier stabilization of the recovery trajectory, while final-quality endpoints remain broadly comparable, and it persists even against a tube-aware block-ranking baseline.