Reconfigurable intelligent surfaces (RIS) are passive controllable arrays of small reflectors that direct electromagnetic energy towards or away from the target nodes, thereby allowing better management of signals and interference in a wireless network. The RIS has the potential for significantly improving the performance of wireless networks. Unfortunately, RIS also multiplies the number of Channel State Information (CSI) coefficients between the transmitter and receiver, which magnifies the challenges in estimating and communicating the channel state information. Furthermore, the simplicity and cost-effectiveness of the passive RIS also implies that the incoming links are not locally estimated at the RIS, and fresh pilots are not inserted into outgoing RIS links. This introduces new challenges for training and estimation of channel state information. The rapid growth of the literature on CSI acquisition in RIS-aided systems has been accompanied by variations in the underlying assumptions, models, and notation, which can obscure the similarities and differences of various techniques, and their relative merits. This paper presents a comprehensive exposition of principles and approaches in RIS channel estimation. The basic ideas underlying each class of techniques are reduced to their simplest form under a unified model and notation, and various approaches within each class are discussed. Several open problems in this area are identified and highlighted.

翻译：重新配置的智能表面(RIS)是小型反射器的被动可控阵列,这些反射器将电磁能量直接引导到目标节点或远离目标节点,从而可以更好地管理信号和干扰无线网络。RIS有可能大大改善无线网络的性能。不幸的是,RIS还使发射机和接收机之间的频道国家信息系数数成倍增加,从而扩大了估计和传送频道状态信息方面的挑战。此外,被动的IRS的简单性和成本效益还意味着,输入的电磁能量的小型反射器不在当地对RIS进行估计,而新的试点也没有插入离场的RIS链接中。这为培训和估计频道状态信息带来了新的挑战。在TRIS援助系统中获取 CSI的文献的迅速增长伴随着基本假设、模型和注释的变化,这些变化可能掩盖各种技术的相似性和差异,以及它们的相对优点。本文对RIS频道估计的原则和方法作了全面的阐述。每个技术类别的基本想法在统一的模型和不同类别中被压缩为最简单的形式。