# A Novel Approach to Enhance the Energy Efficiency of a NOMA Network
## 2 Related Works and Motivation  
Recently, MIMO-NOMA has attracted the attention of many researchers. The authors of [13] presented an iterative algorithm to minimize the overall transmission power. They investigated optimizing power allocation under fixed beam-forming vectors, achieving ideal beam-forming directions based on definite power allocation. Furthermore, a hybrid relaying scheme proposed in [14] can achieve a significant performance gain over conventional NOMA, HD cooperative NOMA (HD-CNOMA) and FD-CNOMA. In [15], the authors presented a full-duplex device-to-device (DdD)-aided cooperative NOMA scheme and derived the outage probability to show the practicality and effectiveness of their design. The authors of [16] discussed the fundamental notion of MIMO-NOMA to indicate the challenges in this domain. Simultaneous wireless information and power transfer (SWIPT) is the key to increasing energy efficiency. In [17], SWIPT was used in composite precoding based on millimeter wave (mmWave) massive MIMO-NOMA. Compared with LTE systems, MIMO-NOMA networks introduce more enhanced spectral efficiency and network capacity with more practical resource allocation algorithms. The authors of [18; 19] investigated resource allocation for NOMA, and their primary emphasis was on sum rate optimization following the total power and proportional rate constraints. The authors of [20] proposed an algorithm to jointly optimize power and channel allocation in NOMA, which significantly optimized throughput and fairness. Regarding ideal channel state information (CSI) at the base station (BS), a near-optimal resolution considering power allocation was proposed in [21]. The authors of [22] presented an effective power allocation design through defective CSI concerning distinct quality-of-service (QoS) conditions. The massive increases in information transfer and wireless end users drive an assured rise in the energy consumption of wireless networks; therefore, energy efficient (EE) schemes for the future generations of wireless systems is of critical concern [23]. Thus, the design of resource allocation schemes with the purpose of enhancing EE has become a vital research topic in NOMA networks. For instance, the authors of [24] analyzed an EE power allocation structure in mmWave massive MIMO with NOMA. Moreover, in [25], the authors investigated an EE transmission design for SISO-NOMA systems. Additionally, the authors of [26] considered a shared power allocation and channel distribution for optimizing the EE of NOMA networks, then later they expanded their work in [27] by introducing a joint subchannel and power optimization structure for a downlink NOMA heterogeneous network that enhances the EE. However, the presented solution concentrated only on increasing the overall EE of networks, driving unbalanced system resource use. The authors of [28] investigated MIMO-NOMA networks for wireless communication networks that aid adaptive multiple access. Three scenarios were used to test and propose innovative adaptive resource allocation mechanisms. An energy efficient strategy for downlink mmWave-NOMA systemswith joint user grouping, scheduling, and optimal power allocation was provided to maximize energy efficiency, proposed by the authors of [29]. This work considers an improved k-means algorithm with NOMA to meet energy efficiency limitations and allocate users to the actual cluster to boost the network sum throughput. The authors of [30] investigated the performance of MC-NOMA technology in an uplink scenario to see how well it can improve system EE by performing energy efficient power and subchannel allocation. They proposed a joint user clustering, subchannel allocation, and power allocation problem to maximize the uplink MC-NOMA scenario's EE (JSPEE). The authors found that the uplink MC-NOMA network's EE performance was significantly improved by utilizing channel gain diversity, even at high minimum data rate parameter values.