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Precoding Design for Drone Small Cells Cluster Network with Massive MIMO: A Game Theoretical Approach

机译:具有大规模MIMO的无人机小型蜂窝集群网络的预编码设计:一种博弈论方法

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The application of drone small cells (DSCs) which are unmanned aerial vehicles (UAVs) carrying communication payload to complete the construction of the high-altitude base stations, is playing an increasingly important role for providing emergent wireless services in different scenarios. In order to coordinate interference and reduce huge backhaul overhead among static ultra-dense DSCs on the low-altitude platform, the paper studies a DSC cluster precoding network with massive multiple-input multiple-output (mMIMO). Considering the disadvantage of the energy-constrained unmanned aerial base station (UABS), we investigate the problem of designing precoding at cluster DSCs to minimize the transmission power of UABSs. A modified cluster scheme based on the Euclidean distance is adopted to cluster the DSCs. We eliminate the intra-cluster interference via performing the modified zero-forcing method and coordinate the inter-cluster interference to achieve our target of reducing transmit power. A non-cooperative game among the DSC clusters is formulated, and the existence and uniqueness of the Nash equilibrium of the proposed game are proved. The non-convex optimization problem is solved via the iterative methods and the numerical results show the effectiveness of our proposed scheme.
机译:无人驾驶飞行器(UAV)无人机小蜂窝小区(DSC)的应用在完成高空基站的建设方面正发挥着越来越重要的作用,以在不同情况下提供紧急无线服务。为了协调低空平台上静态超密集DSC之间的干扰并减少巨大的回程开销,本文研究了具有大规模多输入多输出(mMIMO)的DSC集群预编码网络。考虑到能量受限的无人空中基站(UABS)的缺点,我们研究了在集群DSC上设计预编码以最小化UABS传输功率的问题。采用基于欧氏距离的改进聚类方案对DSC进行聚类。我们通过执行改进的迫零方法消除了集群内干扰,并协调了集群间干扰,以实现降低发射功率的目标。建立了DSC集群之间的非合作博弈,证明了该博弈的纳什均衡的存在性和唯一性。通过迭代方法解决了非凸优化问题,数值结果表明了所提方案的有效性。

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