arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2009.04684eess.SP
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基于张量的mmWave混合圆柱阵多维宽带信道估计

Tensor-based Multi-dimensional Wideband Channel Estimation for mmWave Hybrid Cylindrical Arrays

Zhipeng Lin, Tiejun Lv, Wei Ni, J. Andrew Zhang, Ren Ping Liu

摘要:

信道估计是混合毫米波(mmWave)大规模天线阵列的挑战,其在5G/B5 G应用中是有前途的。这些挑战与混合前端、波束偏斜和对接收机噪声的敏感性造成的角分辨率损失有关。基于张量信号处理理论,提出了一种新的大规模毫米波混合均匀圆柱阵列(UCyAs)多维信道参数估计方法。我们设计了一种新的保持分辨率的混合波束形成器和一种低复杂度的波束斜视抑制方法,并揭示了在UCyA接收阵列信号的张量模型中存在的平移不变性关系。利用这些关系,我们提出了一种新的基于张量的子空间估计算法,以抑制接收机的噪声在所有维度(时间,频率和空间)。该算法可以从相干和非相干信号中准确地估计信道参数。通过Cramér-Rao下界(CRLB)验证,仿真结果表明,该算法在计算复杂度相当的情况下,能够获得比现有的基于矩阵的方法更高的估计精度。

英文摘要:

Channel estimation is challenging for hybrid millimeter wave (mmWave) large-scale antenna arrays which are promising in 5G/B5G applications. The challenges are associated with angular resolution losses resulting from hybrid front-ends, beam squinting, and susceptibility to the receiver noises. Based on tensor signal processing, this paper presents a novel multi-dimensional approach to channel parameter estimation with large-scale mmWave hybrid uniform circular cylindrical arrays (UCyAs) which are compact in size and immune to mutual coupling but known to suffer from infinite-dimensional array responses and intractability. We design a new resolution-preserving hybrid beamformer and a low-complexity beam squinting suppression method, and reveal the existence of shift-invariance relations in the tensor models of received array signals at the UCyA. Exploiting these relations, we propose a new tensor-based subspace estimation algorithm to suppress the receiver noises in all dimensions (time, frequency, and space). The algorithm can accurately estimate the channel parameters from both coherent and incoherent signals. Corroborated by the Cramér-Rao lower bound (CRLB), simulation results show that the proposed algorithm is able to achieve substantially higher estimation accuracy than existing matrix-based techniques, with a comparable computational complexity.

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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