SWIFT-SAT: Efficient and On-Demand Spectrum Coexistence for Satellite-Terrestrial Systems

在新兴应用的推动下，对无线通信的需求不断上升，导致无线电频谱拥堵。该项目为卫星和地面系统之间的频谱共存设计了高效的方案。今天使用的一种频谱共享方法被称为频谱接入系统(SAS)，这是一种集中式数据库和控制系统，它实时地为用户分配信道，以便保护其他用户免受干扰。现有的SAS解决方案在每个设备既发送又接收的情况下支持地面-地面共享。本项目开发的新方案扩展了SAS的概念，以管理卫星-地面频谱共享。该项目解决的关键挑战包括：(A)地面和轨道上的一些设备是无法通过频谱感知检测到的无源接收器，以及(B)SA必须在意识到动态变化的接收器波束的情况下管理多个发射器的聚合干扰。这个项目的发现将为政府政策制定者为开放中频和高频段供频谱共享和商业使用而进行的持续努力提供宝贵的见解。该项目有三个主要研究推动力。第一个推力探索了卫星-地面SA的架构选择。该架构的主要考虑因素包括：有效收集有关系统、位置和波束的数据；高效计算聚合干扰；高效计算共存解决方案，这可能涉及受影响用户运行的可扩展分散算法；以及最大限度地减少对现有卫星系统协议的更改。第二个推力是开发有效的基于SAS的方法来实现卫星系统的干扰保护，包括信道估计和综合干扰计算。考虑的因素包括定向天线、高级干扰管理方案(如MIMO和连续干扰消除)、地形阻塞、空闲时段、部分频谱利用率和基于风险的干扰保护。第三个推力设计了一种多时间尺度共存方案：对于具有固定波束或地面系统的卫星，设计了预计算解；对于具有不可预测波束和移动地面系统的卫星，设计了实时计算解。将初始的非线性优化问题线性化，得到混合整数线性规划(MILP)公式。开发了多种算法来解决MILP问题：使用子问题划分来实现在GPU上的实时优化，使用强化学习来开发低复杂性的算法，以及使用联邦学习来实现跨地面用户网络的分散解决方案。该研究的评估包括对候选体系结构的技术和政策评估，对通道预测的验证，以及共存算法的软件原型。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The escalating demand for wireless communications, fueled by emerging applications, has led to radio spectrum congestion. This project designs efficient schemes for spectrum coexistence between satellite and terrestrial systems. One spectrum sharing approach used today is called a Spectrum Access System (SAS), a centralized database and control system that assigns channels to users in real-time such that other users are protected from interference. Existing SAS solutions support terrestrial-terrestrial sharing in situations where every device transmits as well as receives. The new schemes developed in this project extend the SAS concept to manage satellite-terrestrial spectrum sharing. Key challenges addressed in the project include (a) some devices on the ground and in orbit are passive receivers that cannot be detected by spectrum sensing, and (b) the SAS must manage aggregate interference of multiple transmitters with awareness of dynamically changing receiver beams. The findings from this project will provide valuable insights for ongoing efforts by government policy-makers to open mid-bands and high-bands for spectrum sharing and commercial use.The project has three main research thrusts. The first thrust explores architectural options for the satellite-terrestrial SAS. Key considerations for the architecture include: effective data collection regarding systems, locations, and beams; efficient calculation of aggregate interference; efficient calculation of coexistence solutions, which may involve scalable decentralized algorithms run by affected users; and minimization of changes to existing satellite system protocols. The second thrust develops effective SAS-based methods to achieve interference protection for satellite systems, including channel estimation and aggregate interference computation. Factors considered include directional antennas, advanced interference management schemes such as MIMO and successive interference cancellation, terrain blockage, idle periods, partial spectrum utilization, and risk-based interference protection. The third thrust designs a multi-time scale coexistence scheme: precalculated solutions for satellites with fixed beams or ground systems, and real-time calculated solutions for satellites with unpredictable beams and mobile ground systems. The initially nonlinear optimization problem is linearized to obtain Mixed Integer Linear Program (MILP) formulations. Multiple algorithms to solve the MILP problems are developed: use subproblem partitioning to enable real time optimization on GPUs, use reinforcement learning to develop low-complexity algorithms, and use federated learning to enable decentralized solution across a network of terrestrial users. Evaluation of the research includes technical and policy assessment of candidate architectures, verification of channel predictions, and software prototypes of coexistence algorithms.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.