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arXiv 1609.02660cs.ITmath.IT
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RACE:一种毫米波MIMO系统速率自适应信道估计方法

RACE: A Rate Adaptive Channel Estimation Approach for Millimeter Wave MIMO Systems

Matthew Kokshoorn, He Chen, Yonghui Li, Branka Vucetic

摘要:

在本文中,我们考虑在毫米波(mmWave)无线系统与大型天线阵列的信道估计问题。通过利用毫米波信道固有的稀疏性,我们开发了一种新的速率自适应信道估计(RACE)算法,该算法可以根据估计误差的预期概率(PEE)自适应地调整所需的信道测量的数量。为此,我们设计了一个最大似然(ML)的估计,以最佳的路径信息和相关的错误概率从越来越多的信道测量。基于ML估计器,该算法能够使用可变数量的波束方向图来测量信道,直到接收器相信所估计的方向是正确的。这与现有的毫米波信道估计算法形成对比,在现有的毫米波信道估计算法中,测量的数量通常是固定的。仿真结果表明,与现有的多阶段信道估计算法相比,该算法在保持较高精度的同时,可以显著减少信道估计测量次数。

英文摘要:

In this paper, we consider the channel estimation problem in Millimeter wave (mmWave) wireless systems with large antenna arrays. By exploiting the inherent sparse nature of the mmWave channel, we develop a novel rate-adaptive channel estimation (RACE) algorithm, which can adaptively adjust the number of required channel measurements based on an expected probability of estimation error (PEE). To this end, we design a maximum likelihood (ML) estimator to optimally extract the path information and the associated probability of error from the increasing number of channel measurements. Based on the ML estimator, the algorithm is able to measure the channel using a variable number of beam patterns until the receiver believes that the estimated direction is correct. This is in contrast to the existing mmWave channel estimation algorithms, in which the number of measurements is typically fixed. Simulation results show that the proposed algorithm can significantly reduce the number of channel estimation measurements while still retaining a high level of accuracy, compared to existing multi-stage channel estimation algorithms.

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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