With the combined advantages of satellite communications, aerial networks and terrestrial systems, a space-air-ground integrated network has gradually become a promising architecture for the next generation wireless communication. Due to heterogeneous characteristics of different layers, it is necessary to perform efficient resource allocation. Motivated by this fact, we propose a novel architecture of air-ground integrated networks (AGIN), which leverages civil aircrafts and ground base stations to support terrestrial users’ service. Aiming at maximizing the overall capacity of downlink transmission in an AGIN, we formulate the resource allocation problem as an optimization problem subject to both quality of service (QoS) and fairness requirements. To address the formulated problem, we propose a graph-based joint optimization algorithm for resource block (RB) and power allocation. Specifically, an improved Kuhn-Munkras (KM) algorithm based on graph theory is proposed for RB allocation, which guarantees the fairness. Meanwhile, a multi-level water-filling method is proposed for power allocation. By leveraging an alternating descent approach, a joint optimal solution can be obtained after a finite number of iterations. It is demonstrated through simulation results that the proposed joint optimization algorithm is converges fast and shows significant improvement in terms of the sum-rate, fairness, access latency, and system capacity.

凭借卫星通信，空中网络和地面系统的综合优势，空空地集成网络已逐渐成为下一代无线通信的有前途的体系结构。由于不同层的异构特性，有必要执行有效的资源分配。基于这一事实，我们提出了一种新型的空地综合网络（AGIN）架构，该架构利用民用飞机和地面基站来支持地面用户的服务。为了最大程度地提高AGIN中下行链路传输的整体容量，我们将资源分配问题公式化为同时满足服务质量（QoS）和公平性要求的优化问题。为了解决提出的问题，我们针对资源块（RB）和功率分配提出了一种基于图的联合优化算法。具体而言，提出了一种基于图论的改进的库恩-蒙克拉斯（KM）算法进行RB分配，保证了算法的公平性。同时，提出了一种多级注水分配功率的方法。通过利用交替下降方法，可以在有限次数的迭代之后获得联合最优解。仿真结果表明，所提出的联合优化算法收敛速度快，并且在求和率，公平性，访问延迟和系统容量方面都有显着提高。提出了一种多级注水分配功率的方法。通过利用交替下降方法，可以在有限次数的迭代之后获得联合最优解。仿真结果表明，所提出的联合优化算法收敛速度快，并且在求和率，公平性，访问延迟和系统容量方面都有显着提高。提出了一种多级注水分配功率的方法。通过利用交替下降方法，可以在有限次数的迭代之后获得联合最优解。仿真结果表明，所提出的联合优化算法收敛速度快，并且在求和率，公平性，访问延迟和系统容量方面都有显着提高。