## 2 Related Work  
In [11], the RIS-assisted millimetre wave (mmWave) multi-user system's uplink is examined. By jointly optimizing RIS phase shifts, analog-to-digital converter (ADC) quantization bits, and a beamforming selection matrix under the hardware constraints, the attainable sum capacity is increased. A block coordinated descent (BCD)-based technique is suggested to solve this non-convex problem. It is shown that the proposed BCD algorithm works better than cutting-edge methods. To increase spectrum efficiency, a multi-user uplink with RIS support is recommended in [12]. In this work, a virtual constellation is built using RIS to transmit data from an additional user. By taking into account two users, the analytical average bit error rate (ABER) expressions are obtained. For cost- and power-effective coverage extension, a hybrid transmission strategy combining RIS and decode-and-forward (DF) relays is recommended in [13]. Simulations demonstrate that when used in conjunction rather than as competing technologies, RIS and DF relaying significantly improve rate and error performance. An RIS-aided DF cooperative relaying with energy harvesting is presented in [14]. The effect of spatial correlation between RIS elements is also investigated. In terms of energy harvesting capability and outage probability, the proposed system is analyzed. Finally, index modulation (IM) is added to the idea of joint RIS and DF relaying. For indoor and outdoor environments and various frequency bands, the benefits of RIS deployment are examined in [15]. For both single- and multiple-RIS, the system is tested. It has been demonstrated that RIS-assisted systems greatly enhance achievable rates and error performance for indoor and outdoor environments, as well as different operating frequencies. For orthogonal frequency division multiplexing (OFDM)-based NOMA, a low-complexity user selection and power allocation mechanism is presented in [16]. Users who do not meet the derived criterion are removed. The expressions for closed-form optimal power allocation are derived to maximize the weighted sum capacity of users. The results reveal that the suggested system outperforms the optimal exhaustive user search technique, while being significantly less complex. In [17], NOMA-aided mmWave networks are presented, which can suit the needs of users in a variety of applications. For user association, the Lagrange dual decomposition approach is employed, while power and subcarrier allocation are handled using semi-supervised learning and deep neural networks. The proposed method enhances energy efficiency while meeting the quality of service (QoS), power budget, and interference limitations constraints. The uplink and downlink multiple user power domain NOMA is presented in [18], where it is assumed that the fading links of each user follow distinct distributions, such as Rayleigh, Rician, Nakagami-\(m\), Nakagami-\(q\), \(\kappa-\mu\), and \(\eta-\mu\). Closed-form outage probability expressions are developed for both uplink and downlink, assuming both statistical channel state information and instantaneous channel-based ordering. The simulation results are finally presented to verify the analytical expressions. NOMA can be utilized in land mobile satellite communications to improve coverage and link reliability [19]. Two terrestrial user nodes are used to execute the NOMA uplink, while a satellite is used to do successive interference cancellation (SIC) or joint decoding. The shadowed Rician fading channel is used to develop the closed-form outage probability expressions. Monte-Carlo simulations are performed to validate the closed-form expressions. Downlink NOMA's energy efficiency and fairness are maximized by optimizing subcarrier and power allocation jointly [20]. To accomplish this, a novel greedy subcarrier allocation approach with minimal complexity and fast convergence is proposed. NOMA and cognitive radio (CR) are powerful solutions that address wireless communication's spectrum scarcity issue.