## 1 Introduction  
With the explosion of mobile data and the demand for better quality of service (QoS), effective, and reliable communications are becoming increasingly important. The advent of the internet of things (IoT) marks the interconnection of everything, while providing great convenience. This is a great challenge for information transmission. In the past few decades, researchers have worked to improve the QoS of wireless channels. Now, it is important to find a technology with low energy consumption while ensuring the QoS. The fifth generation (5G) may face problems such as inability to meet larger connection capacity and more energy loss. To solve these problems, the development of the sixth generation (6G) has become a hot topic of increasing interest [1]. The development of 5G has become increasingly saturated, and in the upcoming era of IoT, communication systems need greater spectral efficiency and higher effectiveness. Massive multiple input multiple output (MIMO) technology has become the core technology of 5G, in which a large number of radio frequency (RF) antennas lead to high hardware costs and maintenance costs. The short propagation distance of electromagnetic waves in the high frequency bands and the limited coverage of electromagnetic waves require an increase in the number of base stations (BS), which will further increase the hardware and maintenance costs of 5G. At the same time, the dense distribution of BS and antennas reinforces the signal interference of 5G, deteriorates the performance of the network, increases the computational complexity of network coordination, and creates a serious dilemma in the development of 5G. We need an effective solution to realize the future of 6G [2; 3]. To meet the requirements of superior performance and sustainability 6G, many options have been proposed. Reconfigurable intelligent surface (RIS) has received much attention from academia and industry as a potential technology for 6G. RIS, which is also called intelligent reflecting surface (IRS), is a new paradigm of electromagnetic metamaterials, which is composed of many passive reflective elements. It can reconfigure the wireless communication environment by intelligently modulating electromagnetic waves through digital coding to modulate the amplitude, phase, and frequency of the signal, which can improve the performance of wireless communication systems [4; 5]. In 5G, millimeter wave (mmWave) as one of the main methods can increase the communication capacity to help solve the spectrum shortage problem. However, its small wavelength drawback can lead to transmission difficulties [6]. The coverage capacity of the signal can be increased by arranging RIS. Prior to the proposal of RIS, techniques such as active frequency selective surfaces were proposed [7], followed by theories such as space-time modulated digital coding metasurfaces, which laid the foundation for the emergence of RIS [8]. RIS can increase the network capacity by changing the phase shift to complete passive beam assignment [9]. RIS has been developed continuously and currently there is not only reflective RIS but also transmissive RIS with the advantages of higher aperture efficiency and operating bandwidth [10]. Furthermore, RIS has the advantages of low power consumption and low cost compared with amplify and forward relay system due to its passive characteristics [11]. The above advantages of RIS make it useful in high frequency bands, orthogonal frequency division multiplexing (OFDM) [12], non-orthogonal multiple access (NOMA) [13], and multi-antenna systems. However, to perform the role of RIS and accomplish effective and reliable wireless communication, it is required to obtain accurate channel state information (CSI) using channel estimation techniques, which is a great challenge. There have been many studies in channel estimation, and this paper provides a basic overview of RIS channel estimation. We first analyze the full range of transmitted frequency wireless signals briefly and then focus on the 6G band.