## 5 Numerical and Simulation Results
According to Figure 6, the suggested SSOR-CRZF approach having 4-bit resolution exhibits superior effectiveness when contrasted with competitors. Although it is clearly true that system performance increases as the resolution for PS increases, PSs with high resolution were not necessary due to their added complexity and cost. Figure 7 shows a relative comparison to demonstrate the impact of iteration number associated with the proposed SSOR-CRZF algorithm. As in the figure, for SNR = 15 dB, the SEs (in bps/Hz) for the proposed algorithm with iteration 2, 3, and 4 can be specified as 4.52, 5.11, and 5.63, respectively. It is clear that the increase in the iteration number results in improvement in the SE but at the cost of only a little increase in the complexity. Figure 4: Spectral efficiency of SC-SSOR-CRZF with the variation in \(N_{RF}\) and SNR. Figure 5: SE variation against a number of users. Figure 8 shows the SE of the system as a function of iteration with the following parameters: \(N_{T}=64\), \(N_{RF}=8\), \(K=10\), \(\mathcal{L}=10\), and \(B=4\). Basically, it depicts the relative convergence analysis of the proposed SSOR-CRZF HP-assisted system with its counterparts. This analysis is particularly important as it addresses the core issue of the problem of joint optimization of PA and PS for a system with fixed users (Here, \(K=10\)). Specifically, it depicts that, for the mMIMO-NOMA-SWIPT system, the SC-ZF HP Scheme [3] converges with 7 iterations, while the proposed scheme converges in 8 iterations. It is also important to note that our proposed system converges at a significantly high SE. A comparative analysis of the proposed system with existing work is presented in Figure 9. The results are obtained with the following parameters: \(N_{T}=64\), \(N_{RF}=8\), \(K=10\), \(\mathcal{L}=10\), and \(B=2\). According to the simulation findings, the proposed system outperforms the existing works. Thus, one can observe that the proposed scheme has the potential to significantly improve the SE of the system. Furthermore, the performance of the proposed SSOR-CRZF scheme is explored under the Nakagami-m fading channel and with imperfect CSI. Figure 10 demonstrates the performance comparison of different sub-connected HP schemes with the variation in the Nakagami-m channel fading parameter (\(m\)). For this simulation, we have assumed that each arrival/path is Nakagami-m distributed, contrary to what is assumed in the expanded Saleh-Valenzuela model discussed in Section 2.1. The results are obtained with the following parameters: \(N_{T}=16\), \(N_{RF}=8\), \(K=10\), \(\mathcal{L}=10\), and \(B=4\). This indicates that an increase in the value of \(m\) has a significant impact on the system's SE. As shown, the SE of the system improves as the value of \(m\) increases. Figure 2.0 Spectral efficiency variation with B.  
Figure 2.1 Impact of the iteration number associated with SSOR-CRZF over spectral efficiency. This is because, with \(m=0.5\), the channel can be characterized by a one-sided Gaussian distribution, whereas for \(m=2.0\), it can be described by a Rician distribution. Figure 11 depicts the impact of the imperfect channel on the SE of the system. Following [49], the estimated channel (\(\hat{\mathbf{H}}\)) with CSI error can be modelled as \(\hat{\mathbf{H}}=t\mathbf{H}+\sqrt{1-t^{2}}\mathbf{E}\), where \(t\)\((0\leq t\leq 1)\) is the CSI estimation accuracy and \(\mathbf{E}\) represents error matrix. The results are obtained with the following parameters: \(N_{T}=16\), \(N_{RF}=4\), \(K=6\), \(\mathcal{L}=10\), \(t=0.8\), and \(B=4\). As indicated, the imperfect CSI impacts the performance of the system. More specifically, the SSOR-CRZF scheme provides more stable performance than its counterparts. The EE ((bps/Hz/W)) for the mmWave-mMIMO-NOMA-SWIPT network is displayed in Figure 2.2 As in [3], the EE can be calculated by \(EE=\frac{R_{min}}{P_{T}+N_{RF}P_{T}+N_{SR}P_{S}+P_{R}}\), where \(N_{ps}\) implies the total number of employed phase shifters.