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Resource Allocation and Basestation Placement in Downlink Cellular Networks Assisted by Multiple Wireless Powered UAVs

机译:多无线无人机在下行蜂窝网络中的资源分配和基站布置

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In this paper, we focus on a downlink cellular network, where multiple UAVs serve as aerial basestations to provide wireless connectivity to ground users through frequency division multi-access (FDMA) scheme. The UAVs are exclusively powered by a wireless charging station located on the ground following save-then-transmit protocol. In such a UAV-assisted cellular network, joint optimization for user association, resource allocation and basesation placement are investigated to maximize the downlink sum rate. The problem is formulated as a mixed integer optimization problem and is thus challenging to solve. We propose an efficient solution based on alternating optimization, by iteratively solving one of the three subproblems (i.e., user association, resource allocation and basesation placement) with the other two fixed. Specificly, user association is solved as a standard linear programming problem by relaxing the binary association indicators into continuous variables. For basestation placement and resource allocation, we resort to successive convex optimization technique, which iteratively solves a lower-bound problem. After iteratively solving the three subproblems, we further propose an algorithm based on penalty method and successive convex optimization to make the association indicators feasibly binary. We conduct comprehensive experiments for the optimal solution to the three subproblems with insightful results. We also show that the optimal downlink sum rate cannot be always enhanced by deploying more UAVs due to non-negligible tradeoff between energy/communication sources and co-channel interference. Moreover, the proposed solution outperforms a baseline strategy leveraged from an existing work, especially with favorable channel condition and sufficient frequency resources.
机译:在本文中,我们专注于下行蜂窝网络,其中多个UAV充当空中基站,通过频分多址(FDMA)方案为地面用户提供无线连接。 UAV由保存后传输协议的地面上的无线充电站专门供电。在这种无人机辅助的蜂窝网络中,研究了针对用户关联,资源分配和基站位置的联合优化,以最大化下行链路总和速率。该问题被公式化为混合整数优化问题,因此难以解决。我们提出了一种基于交替优化的有效解决方案,该方法通过迭代解决三个子问题之一(即用户关联,资源分配和基础位置),而另两个问题是固定的。具体而言,通过将二进制关联指示器放宽为连续变量,可以将用户关联作为标准线性规划问题解决。对于基站放置和资源分配,我们采用连续凸优化技术,该技术迭代地解决了一个下界问题。在迭代求解这三个子问题之后,我们进一步提出了一种基于惩罚方法和连续凸优化的算法,以使关联指标可行二元。我们对这三个子问题进行了全面的实验,以找到最佳解决方案,并获得了深刻的结果。我们还表明,由于能量/通信源与同信道干扰之间的权衡不容忽视,无法通过部署更多的无人机来始终提高最佳下行链路总速率。而且,所提出的解决方案优于现有工作所利用的基线策略,尤其是在有利的信道条件和足够的频率资源的情况下。

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