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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2509.01705 |
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| _version_ | 1866908827116371968 |
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| author | Chen, Junting Li, Bowen Sun, Hao Cui, Shuguang Pappas, Nikolaos |
| author_facet | Chen, Junting Li, Bowen Sun, Hao Cui, Shuguang Pappas, Nikolaos |
| contents | The emergence of dense, mission-driven aerial networks supporting the low-altitude economy presents unique communication challenges, including extreme channel dynamics and severe cross-tier interference. Traditional reactive communication paradigms are ill-suited to these environments, as they fail to leverage the network's inherent predictability. This paper introduces predictive communication, a novel paradigm transforming network management from reactive adaptation to proactive optimization. The approach is enabled by fusing predictable mission trajectories with stable, large-scale radio environment models (e.g., radio maps). Specifically, we present a hierarchical framework that decomposes the predictive cross-layer resource allocation problem into three layers: strategic (routing), tactical (timing), and operational (power). This structure aligns decision-making timescales with the accuracy levels and ranges of available predictive information. We demonstrate that this foresight-driven framework achieves an order-of-magnitude reduction in cross-tier interference, laying the groundwork for robust and scalable low-altitude communication systems. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_01705 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Predictive Communications for Low-Altitude Networks Chen, Junting Li, Bowen Sun, Hao Cui, Shuguang Pappas, Nikolaos Signal Processing The emergence of dense, mission-driven aerial networks supporting the low-altitude economy presents unique communication challenges, including extreme channel dynamics and severe cross-tier interference. Traditional reactive communication paradigms are ill-suited to these environments, as they fail to leverage the network's inherent predictability. This paper introduces predictive communication, a novel paradigm transforming network management from reactive adaptation to proactive optimization. The approach is enabled by fusing predictable mission trajectories with stable, large-scale radio environment models (e.g., radio maps). Specifically, we present a hierarchical framework that decomposes the predictive cross-layer resource allocation problem into three layers: strategic (routing), tactical (timing), and operational (power). This structure aligns decision-making timescales with the accuracy levels and ranges of available predictive information. We demonstrate that this foresight-driven framework achieves an order-of-magnitude reduction in cross-tier interference, laying the groundwork for robust and scalable low-altitude communication systems. |
| title | Predictive Communications for Low-Altitude Networks |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2509.01705 |