Integrating Atmospheric Sensing and Communications for Resource Allocation in NTNs

2024-07-09

AI Summary

To address inefficient resource allocation and degraded communication quality in LEO satellite high-frequency links—caused by atmospheric attenuation (e.g., precipitation)—this paper proposes a sensing-assisted communication framework. It pioneers deep integration of atmospheric sensing with communications, establishing a pre-plannable ISAC (Integrated Sensing and Communication) frame structure to enable cross-layer joint optimization. Leveraging real-time atmospheric channel modeling and LEO orbital prediction, the framework jointly optimizes user association, satellite selection, and downlink resource allocation. Compared to conventional decoupled optimization approaches, the proposed scheme achieves a 59% average throughput gain and improves the Jain fairness index by 700%. These results demonstrate substantial enhancements in robustness and spectral efficiency for high-frequency LEO satellite networks under dynamic atmospheric conditions.

Technology Category

• Search and Optimization: Learning to Search
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Constraint Satisfaction and Optimization: Satisfiability

Application Category

• Semantics and Knowledge: Methods to enhance, augment, integrate or synergize semantic models such as knowledge graphs and LLMs
• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization
• Search and Retrieval-Augmented AI: Large language models for search

Abstract

The integration of Non-Terrestrial Networks (NTNs) with Low Earth Orbit (LEO) satellite constellations into 5G and Beyond is essential to achieve truly global connectivity. A distinctive characteristic of LEO mega constellations is that they constitute a global infrastructure with predictable dynamics, which enables the pre-planned allocation of radio resources. However, the different bands that can be used for ground-to-satellite communication are affected differently by atmospheric conditions such as precipitation, which introduces uncertainty on the attenuation of the communication links at high frequencies. Based on this, we present a compelling case for applying integrated sensing and communications (ISAC) in heterogeneous and multi-layer LEO satellite constellations over wide areas. Specifically, we propose a sensing-assisted communications framework and frame structure that not only enables the accurate estimation of the atmospheric attenuation in the communication links through sensing but also leverages this information to determine the optimal serving satellites and allocate resources efficiently for downlink communication with users on the ground. The results show that, by dedicating an adequate amount of resources for sensing and solving the association and resource allocation problems jointly, it is feasible to increase the average throughput by 59% and the fairness by 700% when compared to solving these problems separately.

Problem

• Integrate atmospheric sensing with NTNs for global 5G connectivity.
• Optimize resource allocation in LEO satellite constellations using ISAC.
• Enhance throughput and fairness in downlink communication via sensing.

Innovation

• Integrated sensing and communications (ISAC) framework
• Sensing-assisted resource allocation in LEO constellations
• Joint optimization of throughput and fairness