## 1 Introduction  
Mobile communications face several challenges in delivering signals with a good signal-to-noise ratio (SNR) and high transmission rates to users. One is multipath propagation, which is present mainly in large urban centers, with increasingly larger buildings and many users sharing the spectrum. This study proposes the implementation of strategically positioned reflecting surfaces to enhance the channel SNR and deliver a clearer, less interfered signal. Large, intelligent surfaces have been one of the biggest innovations in digital communications in recent years. The term has variants such as large reflecting surfaces or intelligent reflecting surfaces. They consist of a grid of reflecting units composed of a metamaterial with a controllable reflection coefficient that can be digitally controlled using an optimization algorithm to strengthen the channel's LoS. [PERSON] et al. [1] presented a cost-effective and energy-efficient solution to enhance signal coverage and improve system capacity in mobile communications. However, large intelligent surfaces face challenges such as multiplicative fading effects arising from composite channels between the LIS and base stations and between the LIS and users. Additionally, the LIS encounters difficulties in enhancing communication systems when a strong direct link is present. [PERSON] et al. [2] investigated a scenario where a base station transmits signals to multiple users using a single antenna. They developed an algorithm to jointly optimize power allocation to users and phase shifts induced by the LIS. In contrast to other studies that perform optimization processes in a decoupled manner, the authors propose two solutions: one utilizing linear transformation to reduce the number of variables foroptimization and another employing an element-wise Karush-Kuhn-Tucker approach to derive closed-form expressions for phase shifts in a multi-user scenario. Researchers are actively involved in discussions about the sixth generation and beyond the fifth generation (B5G) of mobile communications in several countries [3; 4; 5; 6]. To meet this advancement, the community faces a series of challenges, encompassing algorithmic and mathematical complexities, as well as issues related to hardware and materials [7; 8; 9; 10]. [PERSON] et al. [11] contributed significantly to addressing the challenges associated with the real-time implementation of LISs. In the same vein, [PERSON] et al. [12] presented a remarkable system proposal employing a reconfigurable smart reflective surface in a MIMO cognitive radio environment. Their approaches strive to optimize the system secrecy rate by jointly optimizing base station transmit beamforming, and RIS-reflected beamforming, considering the complexities of dynamic environments. Despite being a relatively new topic, there are older references in the LIS literature [13]. The term LIS has gained evidence and prominence and become a relevant bet for the technological industry and also academic research as a promising alternative to improve spectral efficiency (since it can act passively, without energy expenditure), decrease the bit error probability, and allow the erasure of channels for eavesdroppers using beamforming techniques, allowing a more elaborate approach of physical layer security. The ability of the LIS to adapt to the channel and generate a resulting channel with different statistics allows us to, in a way, think of a controllable and adjusted channel. The channel between the transmitter and the LIS, as well as the channel between the end-user and the LIS, can be generically modeled using the Nakagami-m distribution, with the \(m\) parameter allowing a generic analysis of the environment's behavior [14] before considering the presence of the LIS. In addition, it is prudent to consider a possible direct channel between the user and the transmitter and channels between the transmitter and an eavesdropper; without losing the generality, we can consider all these channels as Nakagami-m.