The space-air-ground integrated network (SAGIN) is a pivotal architecture to support ubiquitous connectivity in the upcoming 6G era. Inter-operator resource and service sharing is a promising way to realize such a huge network, utilizing resources efficiently and reducing construction costs. Given the rationality of operators, the configuration of resources and services in SAGIN should focus on both the overall system performance and individual benefits of operators. Motivated by emerging symbiotic communication facilitating mutual benefits across different radio systems, we investigate the resource and service sharing in SAGIN from a symbiotic communication perspective in this paper. In particular, we consider a SAGIN consisting of a ground network operator (GNO) and a satellite network operator (SNO). Specifically, we aim to maximize the weighted sum rate (WSR) of the whole SAGIN by jointly optimizing the user association, resource allocation, and beamforming. Besides, we introduce a sharing coefficient to characterize the revenue of operators. Operators may suffer revenue loss when only focusing on maximizing the WSR. In pursuit of mutual benefits, we propose a mutual benefit constraint (MBC) to ensure that each operator obtains revenue gains. Then, we develop a centralized algorithm based on the successive convex approximation (SCA) method. Considering that the centralized algorithm is difficult to implement, we propose a distributed algorithm based on Lagrangian dual decomposition and the consensus alternating direction method of multipliers (ADMM). Finally, we provide extensive numerical simulations to demonstrate the effectiveness of the two proposed algorithms, and the distributed optimization algorithm can approach the performance of the centralized one.

翻译：空天地一体化网络（SAGIN）是支撑即将到来的6G时代泛在连接的关键架构。跨运营商的资源与服务共享是实现这一庞大网络的可行途径，能够高效利用资源并降低建设成本。考虑到运营商的理性，SAGIN中资源与服务的配置应兼顾系统整体性能与运营商个体利益。受新兴共生通信技术（促进不同无线电系统间的互利共赢）的启发，本文从共生通信视角研究SAGIN中的资源与服务共享问题。具体而言，我们考虑由地面网络运营商（GNO）与卫星网络运营商（SNO）构成的SAGIN场景。通过联合优化用户关联、资源分配与波束成形，旨在最大化整个系统的加权和速率（WSR）。同时引入共享系数表征运营商收益。仅以最大化WSR为目标可能导致运营商收益损失。为追求互利共赢，我们提出互利约束（MBC）确保各运营商均能获得收益增长。进而基于逐次凸近似（SCA）方法开发集中式算法，并针对集中式算法实施困难的问题，提出基于拉格朗日对偶分解与共识交替方向乘子法（ADMM）的分布式算法。最后通过大量数值仿真验证两种算法的有效性，结果表明分布式优化算法性能可逼近集中式算法。