# Energy-Efficient User Pairing for Downlink NOMA in Massive MIMO Networks
## 7 Results  
### Performance Evaluation  
In our simulation, the importance of having a correlation between channels must be considered in channel generation. The high correlation helps eliminate interference from other pairs, which improves the weak user's rate. Thus, the correlation between users' channels helps weak users in different pairs have an obvious impact on the system performance metric and highlights the effect of the user pairing process. The simulation parameters applied are introduced in Table 4.  
Figure 2 represents EE for the mMIMO-based scheme presented in [21], compared to EE for NOMA-based scheme with fixed pairing, where users of each pair are specified. Results show that the mMIMO-based scheme achieves higher EE for a lower number of users, where the \(A>>U\) condition is satisfied. The superiority of mMIMO decreases as \(U\) increases till reaching \(U=21\), where the NOMA-based scheme starts to lead. \(A>>U\) is the condition for a system to be considered a massive MIMO system. When this condition is not satisfied with the increasing number of users, the effect of integration of NOMA with massive MIMO on EE improvement is vital. Figure 3 shows EE in bit/joule for different user numbers at a fixed number of BS antennas \(A=36\). The EE increases with increasing \(U\). Results show that correlation-SCP, Hungarian algorithm-SCP, and joint user-RB PA achieve the same EE performance, even with different values of \(U\). They outperform the GSalgorithm-SCP and NOMA-SCP-GA by about 5 M bit/joule with \(U=24\). \begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline Path and penetration loss at distance \(d\) (km) & \(130+37.6\ log_{10}(d)\). \\ \hline Cell edge length & 350 m \\ \hline Coherence interval length (in symbols) & 100 \\ \hline Fixed power: \(P_{fix}\) & 5 W \\ \hline Power of \(BS\)_lo_: \(P_{lo}\) & 0.1 W \\ \hline Power per \(BS\) antennas: \(P_{BS}\) & 0.2 W \\ \hline Power per \(UE\): \(P_{UE}\) & 0.1 W \\ \hline Power for data encoding: \(P_{cod}\) & 0.01 W/(Gbit/s) \\ \hline Power for data decoding: \(P_{dec}\) & 0.08 W/(Gbit/s) \\ \hline \(BS\) computational efficiency: \(L_{bs}\) & 750 Gflops/W \\ \hline Power for backhaul traffic: \(P_{tt}\) & 0.025 W/(Gbit/s) \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Simulation parameters. Figure 4 demonstrates the effect of the increase in the number of BS antennas on EE calculations for different algorithms with \(U=10\) users. The overall performance shows that the increase in \(A\) leads to an increase in EE for low \(A\) values till reaching a value of \(A=20\). Then, the performance changes. EE decreases with increasing \(A\) because the increase in power consumed in a large number of antennas reduces EE, even with the increase in rate. Figure 4: EE versus number of BS antennas, with \(U=10\) users, ZF beamforming. Figure 3: EE versus number of users, with \(A=36\) BS antennas, ZF beamforming. Figure 5 demonstrates the effect of the increase in the number of BS antennas on SE calculations for different algorithms with \(U=10\) users. The overall performance in the results shows that the increase in \(A\) leads to an increase in spectral efficiency. Correlation-SCP, Hungarian algorithm-SCP, and joint user-RB PA have the best performance. NOMA-SCP-GA has the worst performance which means that NOMA groups formed by the greedy algorithm and their allocated power led to the lowest SE results. Figure 6 depicts the power consumed in user pairing algorithms. It shows the high power consumption provided by the correlation-based pairing method as a result of the high computational complexity followed by the swap algorithm used for pairing in (joint user-RB PA) due to the swap process. The GS algorithm and GA algorithm in (NOMA-SCP-GA) achieve the lowest power consumption due to their low computational complexity. The complexity is calculated in Table 5 for the pairing approaches used in our work. Complexity is computed for \(A=36\) BS antennas and \(U=20\) users.