## 1 Introduction
### Resource Allocation Issue for the NOMA System
The fundamental knowledge behind MEC is to leverage base stations and other mobile network infrastructure as compute servers, enabling mobile operators to delegate their most crucial activities to the servers to avoid computationally costly ad delays [57; 58]. Because MEC servers have more processing power than local servers, these computations can be finished faster than locally. Because local computing does not require energy, MEC suggests to offers mobile operators the advantage of longer battery life from a power consumption perspective [59; 60; 61]. MEC is vital in the wireless Internet of Things (IoT) environment,where gadgets usually have limited power and computing capabilities [62]. MEC provides an alternative to employing IoT devices for local task computing for machine learning (ML) applications that is low-latency and power-efficient [63; 64]. The utilization of NOMA for MEC discharge is inspired by the need for spectrally and energy-efficient release in MEC networks [65; 66; 67]. The development of analytical findings for the successful likelihood of MEC discharge demonstrated in [68; 69] that using NOMA communication may momentously decrease the interruption and energy usage of the MEC discharge. The study of the NOMA-centered MEC approach scheme founded on orthogonal frequency division multiplexing (OFDM) in [70; 71; 72; 73] resulted in the creation of state-of-the-art joint power and subcarrier assignment techniques. There was a discussion of utilising unmanned aerial vehicles (UAVs) in NOMA-aided MEC structures [74; 75], and several initiatives for cooperative MEC resource distribution and UAV trajectory schedules were established [76; 77]. The security of NOMA-MEC networks was examined by [78; 79] while assuming that passive eavesdroppers were present. It is shown in [80; 81] that combining MEC with NOMA may avoid time-consuming delays and use less energy. The researchers of [82] also looked at the utilization of uplink and downlink NOMA in MEC structures. The investigators produced investigative outcomes to show how effectively adopting NOMA may decrease the interruption and power usage for MEC discharge. The new emphasis on NOMA and MEC working together is an additional essential communication approach for usage in upcoming wireless networks. The authors of [83] looked at a MEC system that uses NOMA for activity and results downloading while improving communication powers, transmission, time distribution, and work divesting to decrease data consumption. Additionally, [84] combined methods to reduce the total user latency. The authors of [85] adapted multi-antenna NOMA to multi-user MEC systems and considered partial and binary offload situations. Inspired by the advantages of NOMA, substantial studies have been devoted to improving the efficiency of MEC in wireless networks by using NOMA approaches. According to a review of the relevant works, the effectiveness of NOMA-enabled MEC has not been exhaustively examined in various manifold client 6G radiocommunication deployment scenarios. Thus, we evaluated the efficacy of NOMA-enabled MEC expertise utilizing the THz channel for 6G communication. In addition, existing work does not assess the effectiveness of NOMA-centered MEC in a 6G connection employing a THz medium, considering the varying device powers. In this SLR paper, we compare the effectiveness of NOMA-centered MEC systems concerning various key performance parameters, such as resource allocation, power allocation, energy efficiency, dynamic resource allocation, computational efficiency, and computational offloading, for 6G communication deployment scenarios in communities. With a focus on incorporating two concepts relating to NOMA and MEC structures and their utilization in 6G networks, we propose an SLR on NOMA-enabled MEC in this study. NOMA-MEC has emerged as an exciting innovation capable of supporting the growing need for rapid, low-latency, and reliable mobile communication connections.