{"ID":2875565,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2509.02540","arxiv_id":"2509.02540","title":"LLM-Enhanced Space-Air-Ground-Sea Integrated Networks","abstract":"The space-air-ground-sea integrated networking (SAGSIN) concept promises seamless global multimedia connectivity, yet two obstacles still limit its practical deployment. Firstly, high-velocity satellites, aerial relays and sea-surface platforms suffer from obsolete channel state information (CSI), undermining feedback-based adaptation. Secondly, data-rate disparity across the protocol stack is extreme: terabit optical links in space coexist with kilobit acoustic under-water links. This article shows that a single large language model (LLM) backbone, trained jointly on radio, optical and acoustic traces, can provide a unified, data-driven adaptation layer that addresses both rapid CSI ageing and severe bandwidth disparity across the SAGSIN protocol stack. Explicitly, an LLM-based long-range channel predictor forecasts the strongest delay-Doppler components several coherence intervals ahead, facilitating near-capacity reception despite violent channel fluctuations. Furthermore, our LLM-based semantic encoder turns raw sensor payloads into task-oriented tokens. This substantially reduces the SNR required for high-fidelity image delivery in a coastal underwater link, circumventing the data rate limitation by semantic communications. Inclusion of these tools creates a medium-agnostic adaptation layer that spans radio, optical and acoustic channels. We conclude with promising open research directions in on-device model compression, multimodal fidelity control, cross-layer resource orchestration and trustworthy operation, charting a path from laboratory prototypes to field deployment.","short_abstract":"The space-air-ground-sea integrated networking (SAGSIN) concept promises seamless global multimedia connectivity, yet two obstacles still limit its practical deployment. Firstly, high-velocity satellites, aerial relays and sea-surface platforms suffer from obsolete channel state information (CSI), undermining feedback-...","url_abs":"https://arxiv.org/abs/2509.02540","url_pdf":"https://arxiv.org/pdf/2509.02540v1","authors":"[\"Halvin Yang\",\"Sangarapillai Lambotharan\",\"Mahsa Derakhshani\",\"Lajos Hanzo\"]","published":"2025-09-02T17:43:16Z","proceeding":"eess.SP","tasks":"[\"eess.SP\"]","methods":"[\"Large Language Model\",\"Language Model\"]","has_code":false}