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arXiv 1808.07097cs.ITmath.IT
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mmWave无人机网络中NOMA传输的角度反馈

Angle Feedback for NOMA Transmission in mmWave Drone Networks

Nadisanka Rupasinghe, Yavuz Yapici, Ismail Guvenc, Monisha Ghosh, Yuichi Kakishima

摘要:

在本文中,我们考虑一个无人机(UAV)的无线网络使用非正交多址(NOMA)传输毫米波频率提供宽带数据的频谱效率的方式在热点场景。NOMA发射器收集关于用户信道质量的信息的必要性成为实际部署中的主要缺点。因此,我们考虑各种有限的反馈方案的NOMA传输,以减轻跟踪和反馈完整的信道状态信息(CSI)的用户的复杂性。特别是,通过波束成形,我们允许NOMA利用空间域,因此用户角度出现作为一个有前途的(但新颖的)有限的反馈方案。我们表明,随着NOMA传输的用户区域变宽,用户在发射机侧的角度变得更加独特,使得用户角度反馈在这种情况下比距离反馈更好的选择。我们严格推导和分析NOMA传输的中断和速率性能,考虑到各种用户订购策略,包括完整的CSI,角度和距离反馈方案。我们的分析结果NOMA中断总和率使用这些反馈方案匹配密切与模拟,并提供了有用的见解,适当选择有限的反馈方案,不同的部署几何形状和操作配置。

英文摘要:

In this paper, we consider an unmanned aerial vehicle (UAV) based wireless network using non-orthogonal multiple access (NOMA) transmission in millimeter-wave frequencies to deliver broadband data in a spectrally efficient fashion at hotspot scenarios. The necessity for the NOMA transmitter to gather information on user channel quality becomes a major drawback in practical deployments. We therefore consider various limited feedback schemes for NOMA transmission, to relieve the complexity of tracking and feeding back the full channel state information (CSI) of the users. In particular, through beamforming we allow NOMA to exploit the space domain, and hence the user angle emerges as a promising (yet novel) limited feedback scheme. We show that as the user region for NOMA transmission gets wider, the users become more distinctive at the transmitter side with respect to their angles, making user angle feedback a better alternative than distance feedback in such scenarios. We rigorously derive and analyze the outage sum rate performance for NOMA transmission considering various user ordering strategies involving full CSI, angle, and distance feedback schemes. Our analytical results for NOMA outage sum rates using those feedback schemes match closely with simulations, and provide useful insights on properly choosing a limited feedback scheme for different deployment geometries and operating configurations.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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