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arXiv 1403.7870cs.ITmath.IT
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无线能量传输的优化培训设计

Optimized Training Design for Wireless Energy Transfer

Yong Zeng, Rui Zhang

摘要:

射频无线能量传输技术作为一种为能量受限的无线网络提供经济、可靠的电源的解决方案,近年来受到越来越多的关注。为了克服在距离上的显著传播损耗,在能量发射器(ET)处采用多天线以更有效地将无线能量引导到期望的能量接收器(ER)(称为\emph{energy beamforming})是用于实现WET的基本技术。然而,能量波束成形的可实现增益关键地取决于在ET处可用的信道状态信息(CSI),其需要实际获取。在本文中,我们研究了一种有效的信道捕获方法的设计,用于点对点多输入多输出(MIMO)WET系统,通过利用信道的互易性,即,ET经由来自ER的专用反向链路训练来估计CSI。考虑到在ER处的有限能量可用性,训练策略应当被仔细地设计,使得信道能够以足够的准确度被估计,并且还不会在ER处消耗过多的能量。为此,我们建议最大化在ER处的\emph{net}收获的能量,其是用于信道训练的能量的平均收获能量偏移。针对MIMO莱斯衰落信道下的训练设计问题,提出了一个优化问题,包括训练的ER天线子集、训练时间和训练功率的分配。针对一些特殊的情况,得到了封闭形式的解决方案,在此基础上,有用的见解时,应采用训练,以提高在MIMO WET系统的净传输能量。

英文摘要:

Radio-frequency (RF) enabled wireless energy transfer (WET), as a promising solution to provide cost-effective and reliable power supplies for energy-constrained wireless networks, has drawn growing interests recently. To overcome the significant propagation loss over distance, employing multi-antennas at the energy transmitter (ET) to more efficiently direct wireless energy to desired energy receivers (ERs), termed \emph{energy beamforming}, is an essential technique for enabling WET. However, the achievable gain of energy beamforming crucially depends on the available channel state information (CSI) at the ET, which needs to be acquired practically. In this paper, we study the design of an efficient channel acquisition method for a point-to-point multiple-input multiple-output (MIMO) WET system by exploiting the channel reciprocity, i.e., the ET estimates the CSI via dedicated reverse-link training from the ER. Considering the limited energy availability at the ER, the training strategy should be carefully designed so that the channel can be estimated with sufficient accuracy, and yet without consuming excessive energy at the ER. To this end, we propose to maximize the \emph{net} harvested energy at the ER, which is the average harvested energy offset by that used for channel training. An optimization problem is formulated for the training design over MIMO Rician fading channels, including the subset of ER antennas to be trained, as well as the training time and power allocated. Closed-form solutions are obtained for some special scenarios, based on which useful insights are drawn on when training should be employed to improve the net transferred energy in MIMO WET systems.

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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