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The reconfigurable intelligent surface (RIS) has an endless number of application possibilities in terahertz (THz) (Bakht et al., 2019) and millimeter wave (mmWave) systems (Mohammed et al., 2019; Shahjehan et al., 2020). It offers a low-cost, passively controlled hardware structure (Jabeen et al., 2019). Since its introduction, the concept of RIS has gained immediate acceptance in various fields related to wireless communication (Alsafasfeh et al., 2019). An RIS is composed of digitally adjustable passive reflective elements (Narayanan et al., 2018). The system can modify the incident signal’s independent amplitude and/or phase shift to alter the wireless channel used to transport data between the transmitter and receiver (Kotobi et al., 2015). An RIS can therefore modify the wireless propagation environment to enhance signal transmission. Unlike conventional active relay beamforming, an RIS enables full-duplex passive beamforming reflection (Haykin, 2005; Goldsmith et al., 2009; Zhang et al., 2008) and does not require an active radio frequency chain for signal transmission, reception, and self-interference cancellation.
Additionally, owing to its low profile, light weight, and ability to maintain geometry, it can be deployed flexibly and at scale. The RIS has undergone extensive research and has been integrated into various wireless communication environments, including system throughput (Zhao et al., 2008; Yoo & Goldsmith, 2006; Schubert & Boche, 2004), network coverage (Costello, 2009; Qaisar et al., 2020; Tareq et al., 2020), communication security (Nasif et al., 2021; Abdulameer et al., 2020; Fook et al., 2020), communication rate (Alathamneh, 2019; Yan et al., 2016; An et al., 2018; Wu & Zhang, 2020), and channel estimation (Di et al., 2020; Pan et al., 2020; Zheng, et al., 2021; Ramezani & Jamalipour, 2021). This is due to the aforementioned performance attributes of the RIS.
Each passive reflecting element in the uniform planar array of the RIS can slightly alter the amplitude and phase of the incident signal, greatly controlling the signal’s direction and strength at the receiving end (Han, et al., 2022). This feature enables the RIS to assist the system in building an intelligent and reliable edge intelligence system with a higher degree of freedom by helping the system enhance or suppress directional signals according to the needs of each edge agent and forming a fine-grained, three-dimensional passive beam that meets those needs (Hilo et al., 2022; Dong et al., 2021). The RIS has a regulated wireless environment and a collaborative mechanism to allocate resources precisely and effectively. Studies have shown that this technique may significantly enhance the performance of the system in RIS-assisted multiple-input multiple-output (MIMO) systems (Taghavi et al., 2021; Shen, et al., 2021), IRS-assisted orthogonal frequency division multiplexing (OFDM) systems (Li, et al., 2022), IRS-assisted non-orthogonal multiple access (NOMA) systems (Liu et al., 2021), and other systems. Feng et al. (2021) provided a detailed description of IRS-assisted wireless networks, including their key wireless communications applications, benefits over competing technologies, hardware architecture, beamforming design, channel estimation, and network implementation. In terms of theoretical study on data aggregation, Sun & Yan (2021) suggested that to achieve ultra-high-speed data aggregation, the performance of the wireless computing (AirComp) system should be enhanced by deploying IRS. To fully exploit the benefits of the AirComp system, Zheng et al. (2021) recommended integrating IRS into the large-scale cloud radio access network (C-RAN).