In this paper, we study the integration of unmanned aerial vehicle small cells (UAV-SCs) for the purpose of augmenting or temporarily restoring service to an ultra-dense cellular network. The aim is to minimize the overall power consumption of the network by jointly optimizing the number of UAV-SCs, their placement, associations, and the power allocation, subject to user QoS (quality of service), transmit power, and fronthaul capacity constraints. As the resulting optimization problem is non-convex and computationally inefficient to solve, we investigate lower complexity alternatives. By reformulating the original problem, a linear structure can be obtained that is efficiently solved by off-the-shelf solvers. Furthermore, we also propose a meta-heuristic method that is based on particle swarm optimization. The performance of the proposed methods is evaluated via simulation studies and compared to state-of-the-art techniques. The results illustrate that the proposed methods consistently outperform conventional techniques by deploying fewer UAV-SCs and also lowering the transmit powers. Furthermore, considerable power savings were observed particularly for low QoS demands and dense scenarios.

在本文中，我们研究了无人飞行器小型蜂窝（UAV-SC）的集成，目的是增强或暂时恢复超密集蜂窝网络的服务。目的是根据用户QoS（服务质量），发射功率和前传容量约束，通过联合优化UAV-SC的数量，它们的放置，关联和功率分配，以最小化网络的总体功耗。由于由此产生的优化问题是非凸的，并且在计算上效率低下，因此我们研究了较低复杂度的替代方案。通过重新构造原始问题，可以获得一种线性结构，可以通过现成的求解器有效地对其进行求解。此外，我们还提出了一种基于粒子群优化的元启发式方法。通过仿真研究评估了所提出方法的性能，并将其与最新技术进行了比较。结果表明，所提出的方法通过部署较少的UAV-SC并降低发射功率，始终优于传统技术。此外，尤其在低QoS要求和密集场景下，可观地节省了功率。