## 2 Related Works  
In the literature, several methods for increasing the achievable rate in a wireless network can be found. The authors in [11] considered a multi-user IRS-enabled wireless communication system and proposed a novel algorithm for channel estimation. The proposed algorithm demonstrates significant performance enhancement compared to a traditional wireless communication system without IRS and claims to consider practical deployment scenarios. However, for the proposed channel estimation algorithm, the paper does not provide a detailed discussion of the considered practical implementation issues such as hardware limitations, synchronisation requirements and processing overhead. The study [12] explores how big multiple-input multiple-output (MIMO) systems may not be able to transmit wireless data as efficiently as large intelligent surfaces (LIS). The authors propose a new communication paradigm that makes advantage of a considerable quantity of passive reflecting properties in LIS in order to enhance the wireless channel for data transmission. Even though the idea of LIS has received a lot of attention lately, there is not much actual experience with deploying and employing LIS for wireless communication. The major goal of the paper [13] is to give a thorough analysis of the application of IRS in massive MIMO communication systems. The study [14] offers a thorough overview of the most recent advances in secure communications supported by IRS. To address these issues and assess the viability and efficacy of the suggested solutions, additional study is needed. Previous studies have explored enhancements in wireless communication performance through passive beamforming technologies, focusing on improvements in sum-rate, energy efficiency, and reliability. For instance, data rate enhancement was examined in [15], energy-aware design strategies in [16], phase-based reliability improvements without channel state information (CSI) in [17], and latency minimisation under imperfect CSI in [18]. However, joint optimisation of surface placement, phase control, and active beamforming in constrained indoor environments remains insufficiently addressed. To bridge this gap, this work adopts an alternating optimisation framework, where the active beamforming at the transmitter is optimally handled using maximum-ratio transmission (MRT) [19]. In addition to energy and spectrum efficiency, IRS significantly improves throughput and signal quality metrics like SNR and CNR. [PERSON] et al. derived analytical throughput expressions and showed that when IRS functions as a transmitter, it outperforms traditional reflector models by about 1 dB [6]. Other studies suggest that the received SNR can increase with the square--or even fourth power--of the number of IRS elements, thereby enhancing communication reliability and performance [20]. Field trials further confirm these advantages, showing that IRS deployment can increase downlink throughput by 19 to 78 Mbps (up to 360 Mbps). Moreover, IRS is particularly beneficial in NLoS environments, which are prevalent in high-frequency systems like mmWave and terahertz bands. When direct line-of-sight paths are obstructed, IRS can generate alternative paths by reflecting signals strategically, thus preserving link stability. [PERSON] et al. demonstrated that IRS enhances received power and coverage in NLoS conditions, with performance gains scaling with the number of elements [21]. Additionally, IRS-enhanced deployments have shown improvements in reference signal received power (RSRP) by 3-10 dB and better signal quality in challenging environments such as urban shadows and indoor areas [22]. These attributes position IRS as a key enabler for robust and reliable wireless communication in future 6G networks. The primary goal of the paper [23] is to present a thorough analysis of the application of IRS in the context of 6G wireless networks.