## 2 Related Work
In addition, various SIC receivers such as Ideal SIC, Symbol-level SIC, Codeword-level SIC, and Log Likelihood Ratio (LLR)-based receivers are mathematically evaluated and analysed. When NOMA is compared with OMA with simulation results, NOMA showcases its superiority over OMA in terms of KPIs. Furthermore, a survey on the NOMA system is presented in [20], focussing on error rate analysis. The enhanced NOMA strategies, which consist of constellation diagrams, multicarrier systems and detector designs, are discussed, along with research problems and future directions. In [21], a discussion of a deep-learning technique for the NOMA systems is presented. The emphasis is given to deep-learning-based NOMA systems for solving communication issues. These NOMA systems can be integrated with potential technologies such as MEC, MIMO, Intelligent Reflecting Surfaces (IRSs) and Simultaneous Wireless and Information Power Transfer (SWIPT). Also, the focus has been given to KPIs such as SIC, CSI, user fairness and other valuable parameters. Considering the IRS, ref. [22] has addressed the issues related to harnessing the performance of wireless networks in 1G to 5G propagation environments. The issues can be resolved in the Sixth Generation (6G) by employing the IRS with NOMA. The designs and challenges related to IRS-based NOMA systems are comprehensively discussed, with a detailed analysis of the communication framework. In [23], a survey is conducted based on combining the benefits of NOMA and cell-free massive MIMO systems, and a detailed review of how the performance can be increased is included. Moreover, the challenges of combining cell-free massive MIMO systems with other potential technologies are discussed. Visible light communication is a potential solution for high-speed data communications. In [24], the authors have conducted a comprehensive review of NOMA techniques with the involvement of visible light communication systems. They also discussed the limitations and challenges of integrating NOMA with visible light communication systems and the role of machine learning and physical layer security. The authors in [25] have reviewed NOMA-enabled MEC systems in depth, focusing on the issues, challenges and shortcomings that arise. They have claimed that integrating NOMA with MEC will bring unpteen performance characteristics to 5G and B5G communication infrastructures, such as energy efficiency, latency, throughput and massive end-user connectivity. To overcome the issues related to poor channel quality and disconnected communication from BS to users, the work in [26] has analysed the BER and outage probability for multi-hop decode and forward relay-assisted NOMA systems. The BER and outage probability equations are also derived by considering imperfect SIC and CSI. The proposed model's simulation results depict the superiority over traditional OMA systems. The authors in [9] have focussed on efficient strategies to integrate NOMA into 5G and 6G systems. This integration can be beneficial for UL and DL application environments under the 3 rd Generation Partnership Project (3 GPP) standardisation. The author in [27] has focussed on optimising PA coefficients to gain optimum proportional fairness in PD-NOMA transmission with complete or limited SIC. The numerical results illustrate the impact of complete or limited SIC on the system performance with sum rate loss due to proportional fairness. Similarly, ref. [28] considers a hybrid automatic repeat request protocol for PD-NOMA with proportional fairness on the fading channel. It analyses the system performance for different symmetric and asymmetric scenarios concerning throughput, outage probabilities and delays with varying PA.