As an attractive enabling technology for next-generation wireless communications, network slicing supports diverse customized services in the global space-air-ground integrated network (SAGIN) with diverse resource constraints. In this paper, we dynamically consider three typical classes of radio access network (RAN) slices, namely high-throughput slices, low-delay slices and wide-coverage slices, under the same underlying physical SAGIN. The throughput, the service delay and the coverage area of these three classes of RAN slices are jointly optimized in a non-scalar form by considering the distinct channel features and service advantages of the terrestrial, aerial and satellite components of SAGINs. A joint central and distributed multi-agent deep deterministic policy gradient (CDMADDPG) algorithm is proposed for solving the above problem to obtain the Pareto optimal solutions. The algorithm first determines the optimal virtual unmanned aerial vehicle (vUAV) positions and the inter-slice sub-channel and power sharing by relying on a centralized unit. Then it optimizes the intra-slice sub-channel and power allocation, and the virtual base station (vBS)/vUAV/virtual low earth orbit (vLEO) satellite deployment in support of three classes of slices by three separate distributed units. Simulation results verify that the proposed method approaches the Pareto-optimal exploitation of multiple RAN slices, and outperforms the benchmarkers.

翻译：作为下一代无线通信中的关键赋能技术，网络切片能够在具有多样化资源约束的全球空天地一体化网络中支持各类定制化服务。本文在相同的底层物理空天地一体化网络架构下，动态考虑三类典型的无线接入网切片，即高通量切片、低时延切片和广覆盖切片。通过结合空天地网络地面、空中及卫星组件的差异化信道特征与服务优势，以非标量形式对这三类无线接入网切片的吞吐量、服务时延和覆盖面积进行联合优化。提出一种联合中心与分布式的多智能体深度确定性策略梯度算法来解决上述问题，以获得帕累托最优解。该算法首先通过中心单元确定虚拟无人机最优位置及切片间子信道与功率共享方案，随后通过三个独立分布式单元分别优化切片内子信道与功率分配，以及支持三类切片的虚拟基站/虚拟无人机/虚拟低轨卫星部署。仿真结果验证了所提方法能接近多类无线接入网切片的帕累托最优利用，性能优于基准方案。