Similarly, the authors of [15] studied the outage performance and the matching problem along with power allocation and decoding order ranges of a downlink system scenario, where the transmitter aims to send independent data to the receivers with specific data rates under the effect of statistically generated CSI. In [16], an analysis of the NOMA outage performance was performed under two conditions: The QoS requirement of the corresponding data rate of users, and the channel's signal-to-noise ratio (SNR) for each user. The developed analytical results proved that NOMA can achieve superior performance in terms of users' data rates. Thus, choosing the users' targeted data rates and allocated power affects the outage performance of NOMA. The channel exhibited small-scale Rayleigh fading and the power coefficients were limited to a single value per user. The authors [16] found that the performance of NOMA at low SNR values was insignificant. In [17], the authors investigated variations in the outage probability and throughput against variable SNR values and under the impact of imperfect CSI using the minimum mean square error (MMSE) for channel estimation, but the calculation and assignment of power coefficients was not explained. The authors of [17] calculated the outage probability at a fixed distance from the base station (BS) and proposed a channel estimation method that was not adaptive to changes in the channel's response. The authors of [18] studied the performance of the NOMA system in both the uplink and downlink by comparing the spectral efficiency of NOMA with respect to OMA systems. The authors of [18] mainly predicted a relation between the user selection criteria and the distance from the serving base transceiver station (BTS), taking into consideration the spectral efficiency of the system under an invariant channel. The authors of [19] aimed to maximize the sum rate in visible light communication (VLC) downlink NOMA systems by proposing a fair, non-complex optimum power allocation algorithm. In [20], the authors determined a closed-form expression for the optimum power allocation algorithm based on maximizing the sum rates in a single-input-single-output (SISO) downlink NOMA system. The authors proved that to reach the optimum solution, each user is required to decode the messages of users with lower SNRs first. The authors in [18] did not propose any channel estimation schemes to illustrate the effect of the channel conditions on the results obtained and only focused on varying the distance of the users from the BS to study the interference among users, rather than varying the signal power levels of the users. The authors of [2; 4; 21; 22; 23] surveyed all proposed NOMA algorithms, including single carrier, multi carrier, power domain (PD), and cognitive radio-NOMA (CR-NOMA) as well as SISO and multiple-input-multiple-output (MIMO) NOMA. The main difference between NOMA and MIMO systems is that in MIMO, the system uses multiple antennas to transmit and receive the signals, while NOMA combines the signals as an SISO system with a single transmitting and receiving antenna [3]. The authors in [24] studied the MIMO NOMA system from the single carrier's point of view; the authors compared the BER performance and the power efficiency of the proposed NOMA model in downlink transmission to the theoretical NOMA and OMA performance. This results in a high-power efficiency system as well as an improved system performance. The authors of [2] discussed the modulation and coding schemes that could be proposed in future NOMA systems as well as the security matters in NOMA and the applications of NOMA in future radio generations. The authors in [25] studied the performance of cooperative modulation-based NOMA, where the authors proposed a modulation scheme based on QPSK. The proposed modulation scheme guarantees orthogonality between users through modulation of the near users on the real component and the far users on the imaginary component.