In this paper, a channel estimation technique for reconfigurable intelligent surface (RIS)-aided multi-user multiple-input single-output communication systems is proposed. By deploying a small number of active elements at the RIS, the RIS can receive and process the training signals. Through the partial channel state information (CSI) obtained from the active elements, the overall training overhead to estimate the entire channel can be dramatically reduced. To minimize the estimation complexity, the proposed technique is based on the linear combination of partial CSI, which only requires linear matrix operations. By exploiting the spatial correlation among the RIS elements, proper weights for the linear combination and normalization factors are developed. Numerical results show that the proposed technique outperforms other schemes using the active elements at the RIS in terms of the normalized mean squared error when the number of active elements is small, which is necessary to maintain the low cost and power consumption of RIS.

翻译：本文提出了一种适用于可重构智能表面辅助的多用户多输入单输出通信系统的信道估计技术。通过在可重构智能表面部署少量有源单元，该表面能够接收并处理训练信号。利用从有源单元获取的部分信道状态信息，可以显著降低估计整个信道所需的整体训练开销。为最小化估计复杂度，所提技术基于部分信道状态信息的线性组合，仅需线性矩阵运算。通过利用可重构智能表面单元间的空间相关性，设计了用于线性组合的适当权重及归一化因子。数值结果表明，在有源单元数量较少（这对保持可重构智能表面的低成本与低功耗至关重要）的情况下，所提技术在归一化均方误差方面优于其他利用可重构智能表面有源单元的方案。