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Spectral Efficiency Maximization for Multiuser MISO-NOMA Downlink Systems with SWIPT

机译:带有SWIPT的多用户MISO-NOMA下行链路系统的频谱效率最大化

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In this paper, we study the problem of jointly optimizing user pairing and beamforming design in multiuser multiple-input single-output (MU-MISO) non-orthogonal multiple access (NOMA) downlink systems with simultaneous wireless information and power transfer (SWIPT). Aiming at maximizing the achievable sum throughput subject to energy harvesting (EH) constraints, we propose a hybrid user pairing beamforming scheme (HBS), where two users with distinct channel conditions are optimally selected to perform user pairing. Moreover, we adopt a non-linear EH model for energy users to reveal their practical circuit characteristics. The sum throughput problem is formulated as a class of mixed-integer nonconvex optimization programming which is computationally prohibitive. To solve this challenging problem, we propose a low-complexity iterative algorithm, yet efficient, based on sequential convex approximation method to arrive at least the local optima. Numerical results are provided to demonstrate the performance improvement of the proposed HBS scheme over the multiuser beamforming one without user pairing, revealing to be an effective scheme for MU-MISO-NOMA downlink systems.
机译:在本文中,我们研究了在同时具有无线信息和功率传输(SWIPT)的多用户多输入单输出(MU-MISO)非正交多路访问(NOMA)下行链路系统中共同优化用户配对和波束成形设计的问题。为了最大化在能量收集(EH)约束下可实现的总吞吐量,我们提出了一种混合用户配对波束成形方案(HBS),其中最佳选择了具有不同信道条件的两个用户来执行用户配对。此外,我们为能源用户采用了非线性EH模型,以揭示他们的实际电路特性。和吞吐量问题被表述为一类混合整数非凸优化编程,它在计算上是令人望而却步的。为了解决这一难题,我们提出了一种基于序列凸逼近法的低复杂度迭代算法,但效率很高,至少可以达到局部最优。数值结果证明了所提出的HBS方案相对于没有用户配对的多用户波束形成方案的性能改进,这是MU-MISO-NOMA下行链路系统的有效方案。

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