In this paper, we investigate time-division based framework for integrated sensing, communication, and computing in integrated satellite-terrestrial networks. We consider a scenario, where Internet-of-Things devices on the ground operate with sensing and communication in a time-division manner, and can process the sensing results locally, at the edge, or in the cloud via the satellite communication link. Based on the proposed framework, we formulate a multi-dimensional optimization problem to maximize the utility performance of sensing, communication, and computing abilities. After decomposing the original optimization problem into two subproblems, we first derive the closed-form solution of the optimal task partitioning strategy for terrestrial users and satellite users. Then, we develop the joint subframe allocation and task partitioning strategy to optimize the overall performance, by means of which the Pareto optimal solutions can be obtained along the Pareto frontier. Extensive simulations are provided to demonstrated the effectiveness of the proposed strategy, which is 10% to 60% superior compared with the benchmarks. Also, the trade-off between the multidimensional resource and multi-functional performance is analyzed from the perspective of network design.

翻译：本文研究了面向集成卫星-地面网络（ISTN）的时分协同感知-通信-计算一体化框架。我们考虑地面物联网设备采用时分方式协同完成感知与通信任务，并可通过卫星通信链路在本地、边缘端或云端处理感知结果。基于所提框架，我们构建了一个多维优化问题以最大化感知、通信与计算能力的联合性能。通过将原优化问题分解为两个子问题，首先推导出地面用户与卫星用户最优任务分配策略的闭式解，继而提出联合子帧分配与任务分配策略以优化整体性能，沿帕累托前沿获取多目标最优解。大量仿真验证表明，所提策略相比基准方案可实现10%至60%的性能提升。此外，从网络设计角度分析了多维资源与多功能性能之间的折中关系。