论文标题

在存在多路径的情况下,多用户光束对齐

Multi-user Beam Alignment in Presence of Multi-path

论文作者

Torkzaban, Nariman, A., Mohammad, Khojastepour, Baras, John S.

论文摘要

为了克服高路径损失和毫米波(mmwave)通信的剧烈阴影,需要有效的光束形成方案,这将融合具有屏蔽型的狭窄光束。 MMWave通道由几个与一个出发角度(AOD)相关的空间簇组成。狭窄的光束必须与通道AOD对齐,以增加光束形成的增益。这是通过称为梁对准(BA)的程序来实现的。文献中的大多数BA方案都考虑具有单个主导路径的通道,而在实践中,该通道具有一些具有不同AOD的可分离路径,因此,此类BA方案可能无法正确地工作,或者在存在多路径的情况下可能无法正常工作,或者至少没有利用此类多径以实现多样性或增加鲁棒性。 在本文中,我们提出了一个有效的BA方案,在存在多路径的情况下。所提出的BA方案使用一组扫描梁传输探测数据包,并在每个用户的探测阶段结束时收到所有扫描梁的反馈。我们将BA方案制定为最小化不同策略下平均透射横梁宽度的预期值。该策略定义为从接收反馈到一组传输梁(TB)的函数。为了最大程度地提高可能的反馈序列的数量,我们证明了一组扫描梁(SB)具有特殊的形式,即郁金香设计。因此,我们使用一组线性约束和减少的变量来重写最小化问题,并通过使用有效的贪婪算法来解决。

To overcome the high path-loss and the intense shadowing in millimeter-wave (mmWave) communications, effective beamforming schemes are required which incorporate narrow beams with high beamforming gains. The mmWave channel consists of a few spatial clusters each associated with an angle of departure (AoD). The narrow beams must be aligned with the channel AoDs to increase the beamforming gain. This is achieved through a procedure called beam alignment (BA). Most of the BA schemes in the literature consider channels with a single dominant path while in practice the channel has a few resolvable paths with different AoDs, hence, such BA schemes may not work correctly in the presence of multi-path or at the least do not exploit such multipath to achieve diversity or increase robustness. In this paper, we propose an efficient BA scheme in presence of multi-path. The proposed BA scheme transmits probing packets using a set of scanning beams and receives feedback for all the scanning beams at the end of the probing phase from each user. We formulate the BA scheme as minimizing the expected value of the average transmission beamwidth under different policies. The policy is defined as a function from the set of received feedback to the set of transmission beams (TB). In order to maximize the number of possible feedback sequences, we prove that the set of scanning beams (SB) has a special form, namely, Tulip Design. Consequently, we rewrite the minimization problem with a set of linear constraints and a reduced number of variables which is solved by using an efficient greedy algorithm.

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