Collaborative Multi-Resource Allocation in Terrestrial-Satellite Network Towards 6G
Collaborative Multi-Resource Allocation in Terrestrial-Satellite Network Towards 6G
复制标题
DOI：
10.1109/twc.2021.3080578
复制
发表时间：
2021-11-01
影响因子：
10.4
通讯作者：
Zhao, Lian
中科院分区：
文献类型：
--
作者：
Fu, Shu;Gao, Jie;Zhao, Lian
地面卫星网络（TSN）被设想在第六代（6G）无线网络中发挥重要作用。在这样的网络中，热气球很有用，因为它们可以在卫星和地面站之间中继信号。大多数现有的工作假设热气球部署在相同的高度，具有相同的最小仰角到卫星，这可能是不切实际的，由于可能的路线冲突与飞机和其他飞行设备。在本文中，我们考虑一个TSN包含在不同的高度和不同的最小仰角的热气球，这创造了不均匀的可用服务时间的热气球和卫星之间的通信的挑战。联合考虑缓存，计算和通信（3C）资源管理的地面气球卫星链路和卫星间激光链路，我们的目标是最大限度地提高网络的能源效率。首先，提出了一种自来水注水算法，根据卫星的可用服务时间，对卫星间的业务进行调度。然后，我们生成一系列的配置矩阵，在此基础上，我们制定的中继时间和功耗之间的关系，在卫星之间的中继。最后，对TSN的协同资源分配问题进行了建模，并采用泰勒级数近似的几何规划方法进行了求解。仿真结果证明了该方案的有效性。
Terrestrial-satellite networks (TSNs) are envisioned to play a significant role in the sixth-generation (6G) wireless networks. In such networks, hot air balloons are useful as they can relay the signals between satellites and ground stations. Most existing works assume that the hot air balloons are deployed at the same height with the same minimum elevation angle to the satellites, which may not be practical due to possible route conflict with airplanes and other flight equipment. In this paper, we consider a TSN containing hot air balloons at different heights and with different minimum elevation angles, which creates the challenge of non-uniform available serving time for the communication between the hot air balloons and the satellites. Jointly considering the caching, computing, and communication (3C) resource management for both the ground-balloon-satellite links and inter-satellite laser links, our objective is to maximize the network energy efficiency. Firstly, by proposing a tapped water-filling algorithm, we schedule the traffic to relay among satellites according to the available serving time of satellites. Then, we generate a series of configuration matrices, based on which we formulate the relation between relay time and the power consumption involved in the relay among satellites. Finally, the collaborative resource allocation problem for TSN is modeled and solved by geometric programming with Taylor series approximation. Simulation results demonstrate the effectiveness of our proposed scheme.