## 1 Introduction  
As mobile communication evolves, every new generation introduces new features, especially for the higher transmission rate. The demands for 5G are still evolving, and complete 5G infrastructure is getting rolled out. The researchers are working on 6G, anticipating demands based on future needs [1]. An Intelligent Reflecting Surface (IRS) is an umbrella term that appeared recently in the electromagnetic [2, 3] and wireless domains [4]. Reflecting surfaces, also known as intelligent or reconfigurable surfaces, can play a significant role in 5G and potential future 6G communication networks [5, 6]. These reflecting surfaces are periodic and designed to manipulate the transmission of electromagnetic waves to enhance wireless communication in various ways. An IRS is a two-dimensional structural array of metamaterial cells and, by tuning impedance variations over the cluster of the unit cell surface, the interaction with incident electromagnetic waves can be controlled [7]. For the enhancement of the wireless communication systems of the 5G and especially the 6G networks, an IRS plays an significant role. In the evolution of cellular technology up until 5G, the channel was deemed to be uncontrollable, and the focus was mainly on spectral efficiency and antennas. But recently, the IRS has attracted emerging technological attention, and is regarded as an innovative tech infrastructure for the beyond fifth-generation (B5G)communication systems because of its potential to achieve significant improvement in communication coverage, latency, throughput, device density, and energy efficiency.The work in [8] lists the five emerging antenna array research directions. The work illustrates the possible solutions to achieve the high speed and coverage problems. The IRS phase shift model, explained in [9], helps in the beamforming of the incident EM waveform to the receiver. An IRS comprises low-cost periodic reflecting elements mounted on a planar surface. These metasurfaces can be used in 6G communication systems to direct incident wireless signals from a transmitter towards a receiver. It can achieve 3-D passive beamforming via joint signal reflection [10]. The studies in [11] propose a low-complexity framework for channel estimation and passive beamforming in RIS-assisted Multiple-Input and Multiple-Output (MIMO) systems. The approach involves partitioning the channel training phase and pre-designing RIS reflection coefficients to estimate the effective superposed channel, thus reducing complexity. The framework optimizes RIS reflection by selecting from a pre-designed training set to maximize achievable rates. Novel methods for generating RIS reflection coefficient training sets are introduced, showing significant performance benefits over traditional methods, especially in fast-changing channels with limited coherence time. The results demonstrate the proposed framework's competitive advantage in terms of complexity, pilot overhead, and signaling requirements. The work in [12] explores codebook-based solutions for a RIS in wireless communication, focusing on channel estimation and passive beamforming challenges. It introduces a framework that uses a pre-designed codebook for RIS reflection patterns, reducing pilot signaling overhead and complexity. This method enhances energy efficiency, scalability, and system performance, providing a practical approach for RIS-assisted communication systems without relying on complex model assumptions. The studies in [13] introduced a novel approach leveraging stacked intelligent metasurfaces (SIMs) for advanced signal processing in the electromagnetic wave domain. This SIM-based system aims to enhance holographic MIMO (HMIMO) communications by integrating multiple metasurface layers at both the transmitter and receiver ends, effectively minimizing the need for numerous RF chains. The proposed system optimizes the phase shifts of the metasurface layers to create interference-free parallel subchannels, significantly improving channel capacity and performance.