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Energy-Aware 3D Aerial Small-Cell Deployment over Next Generation Cellular Networks

机译:下一代蜂窝网络上的能源感知3D空中小型蜂窝部署

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One viable and cost-effective method to fulfill the ever-increasing mobile broadband traffic and to achieve coverage and capacity improvement is the employment of mobile small cells in next generation cellular networks. Being agile and resilient, aerial small cells (ASCs), which are small cells mounted on unmanned aerial vehicles (UAVs), are deemed promising platforms for the provision of wireless services. Since the lifetime of an airborne network highly depends on the residual battery capacity available to each ASC, it is essential to account for the energy expenditure on various flying actions in a flight plan. Therefore, the focus of this paper is to study the 3D deployment problem for a swarm of ASCs, in which a trade-off among flight altitudes, energy expenses and available lifetimes is observed. The objective is to maximize the total throughput of all users. We formulate the problem as a non-convex non-linear optimization problem and propose an energy-aware 3D deployment algorithm to resolve it with the aid of Lagrangian dual relaxation, interior-point and subgradient projection methods. We then conduct a series of simulations to evaluate the performance of our proposed algorithm. Simulation results manifest that our proposed algorithm can bring tremendous increase in the total throughput for all users by properly coping with the trade-off, compared to the two user-aware approaches with random and minimum altitude assignments.
机译:满足不断增长的移动宽带流量并实现覆盖和容量提高的一种可行且具有成本效益的方法是在下一代蜂窝网络中使用移动小蜂窝。空中小小区(ASC)具有敏捷性和弹性,是安装在无人飞行器(UAV)上的小小区,被认为是提供无线服务的有前途的平台。由于机载网络的寿命在很大程度上取决于每个ASC可用的剩余电池容量,因此必须在飞行计划中考虑各种飞行动作的能量消耗。因此,本文的重点是研究大量ASC的3D部署问题,其中观察到了飞行高度,能耗和可用寿命之间的权衡。目的是使所有用户的总吞吐量最大化。我们将该问题公式化为非凸非线性优化问题,并提出了一种能量感知的3D部署算法,以借助Lagrangian对偶弛豫,内点和次梯度投影方法来解决该问题。然后,我们进行一系列仿真,以评估我们提出的算法的性能。仿真结果表明,与两种具有随机和最小高度分配的用户感知方法相比,通过适当地权衡取舍,我们提出的算法可以为所有用户带来总吞吐量的极大提高。

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