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Energy Efficiency Maximization in Massive MIMO-NOMA Networks with Non-linear Energy Harvesting

机译:具有非线性能量收集的大规模MIMO-NOMA网络中的能效最大化

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This paper investigates the energy-efficient resource allocation problem in massive multiple input and multiple output (MIMO) non-orthogonal multiple access (NOMA) networks with practical non-linear energy harvesting (NEH). In the considered system, a multi-antenna base station (BS) transfers power to the Internet-of-Things (IoT) devices via energy beamforming in the downlink, followed by the IoT devices sending their data simultaneously in the uplink by consuming the harvested energy. A time division protocol is designed to adequately allocation the energy harvesting (EH) time and wireless information transmission time. To improve the energy efficiency (EE), we propose a joint power, time and antenna selection allocation scheme under the NEH model. An EE maximization problem is formulated to effectively determine the optimal resource allocation strategies. As the formulated problem is non-trivial, a non-linear fraction programming method is applied to convert the problem into a convex optimization problem, and then solve it by Lagrange dual decomposition approach. Simulation results demonstrate the effectiveness of the proposed solution.
机译:本文研究了具有实际非线性能量收集(NEH)的大规模多输入和多输出(MIMO)非正交多址(NOMA)网络中的能力资源分配问题。在所考虑的系统中,多天线基站(BS)通过下行链路中的能量波束形成通过能量波束形成来传送到内容物体的电源,然后通过消耗收获,在上行链路中同时发送数据的IOT设备活力。时分协议旨在充分分配能量收集(EH)时间和无线信息传输时间。为了提高能效(EE),我们提出了NEH模型下的接合电力,时间和天线选择分配方案。制定EE最大化问题以有效地确定最佳资源分配策略。由于配制的问题是非琐碎的,应用非线性分数编程方法将问题转换为凸优化问题,然后通过拉格朗日双分解方法来解决它。仿真结果证明了所提出的解决方案的有效性。

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