A reconfigurable intelligent surface (RIS) consists of massive meta elements, which can improve the performance of future wireless communication systems. Existing RIS-aided channel estimation methods try to estimate the cascaded channel directly, incurring high computational and training overhead especially when the number of elements of RIS is extremely large. In this letter, we propose a cost-efficient channel estimation method via rank-one matrix factorization (MF). Specifically, if the RIS is employed near base station (BS), it is found that the RIS-aided channel can be factorized into a product of low-dimensional matrices. To estimate these factorized matrices, we propose alternating minimization and gradient descent approaches to obtain the near optimal solutions. Compared to directly estimating the cascaded channel, the proposed MF method reduces training overhead substantially. Finally, the numerical simulations show the effectiveness of the proposed MF method.

中文翻译：

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通过一级矩阵分解的成本高效的 RIS 辅助信道估计

可重构智能表面（RIS）由大量元元素组成，可以提高未来无线通信系统的性能。现有的 RIS 辅助信道估计方法试图直接估计级联信道，会产生很高的计算和训练开销，尤其是当 RIS 的元素数量非常大时。在这封信中，我们通过秩一矩阵分解 (MF) 提出了一种具有成本效益的信道估计方法。具体而言，如果在基站（BS）附近采用RIS，则发现RIS辅助信道可以分解为低维矩阵的乘积。为了估计这些分解矩阵，我们提出交替的最小化和梯度下降方法来获得接近最优的解决方案。与直接估计级联信道相比，所提出的 MF 方法大大减少了训练开销。最后，数值模拟表明了所提出的MF方法的有效性。