## 5 Results and Discussion
\(\dot{R}^{i}_{s,p}=1\) and \(\dot{R}^{i}_{w,p}=1\) are established for throughput analysis, with throughput achieving 2 bps/Hz at a high SNR. It is observed that at a low SNR, the performance of NN-FF pairing dominates over other schemes. As the SNR increases, SW-SW pairing shows improved performance. This illustrates the trade-off between computational complexity and performance. Increased computational complexity necessitates more processing power and time to execute pairing, resulting in higher SNR requirements. Based on the SNR region, appropriate pairing can be applied. At an SNR of \(-15\) dB, NN-FF, OO-EE, SW, RP-1, RP-2, RP-3, and SW-SW achieve throughputs of \(\sim\)0.111, \(\sim\)0.089, \(\sim\)0.063, \(\sim\)0.054, \(\sim\)0.030, \(\sim\)0.027, and \(\sim\)0.026 bps/Hz, respectively. Here, NN-FF  
Figure 10: Average probability of outage of the SW-SW WUE under iSIC, \(\varepsilon~{}=~{}0.01\), and HWDs for varying \(L\). Figure 9: Average probability of outage of the SW-SW SUE under iSIC, \(\varepsilon~{}=~{}0.01\), and HWDs for varying \(L\). shows a difference of \(\sim\)0.022 to \(\sim\)0.085 bps/Hz in throughput over other pairing schemes. NN-FF pairing demonstrates improved performance at an SNR of \(-\)15 dB because it has the lowest complexity order compared to other pairing schemes. However, for an SNR of \(-\)2 dB, NN-FF, OO-EE, SW, RP-1, RP-2, RP-3, and SW-SW achieve throughputs of \(\sim\)1.538, \(\sim\)1.592, \(\sim\)1.624, \(\sim\)1.644, \(\sim\)1.681, \(\sim\)1.687, and \(\sim\)1.719 bps/Hz, respectively. At a \(-\)2 dB SNR, SW-SW provides \(\sim\)0.032 to \(\sim\)0.181 bps/Hz difference in throughput over other pairing schemes. From Figure 11, it can be inferred that based on the application and requirement, a less complex NN-FF pairing can be chosen where performance is compromised, while for performance-oriented applications, SW-SW pairing can be applied, which may incur higher power consumption due to computational complexity. Figure 12 illustrates the throughput performance of SW-SW pairing under various \(L\) values while increasing HWDs under a fixed SIC error of 0.01. From Figure 12, it is apparent that throughput performance degrades as HWD increases. An increase in \(L\) results in enhanced throughput performance. Table 7 shows the throughput performance of SW-SW pairing under iSIC and HWDs for different \(L\) values. Table 7 shows that as HWD increases, the SNR requirement increases. These findings reveal a significant relationship: as HWD grows, the required SNR for optimal performance also increases. This trend emphasizes the importance of considering HWD conditions when optimizing system performance. From Table 7, we see that an increase in the effect of HWD leads to a degradation in throughput performance. To mitigate the losses from iSIC and HWD conditions, a large \(L\) is utilized, resulting in a significant enhancement in throughput performance. At \(d\) = 0.08, the SNR gain recorded with \(L\) = 256 ranges from \(\sim\)14.04 to \(\sim\)20.91 dB with \(L\) = 64 and 32, respectively. At \(d\) = 0.09, the SNR gain recorded with \(L\) = 256 ranges from \(\sim\)14.01 to \(\sim\)20.76 dB with \(L\) = 64 and 32, respectively. Similarly, at \(d\) = 0.15, the SNR gain recorded with \(L\) = 256 ranges from \(\sim\)14.03 to \(\sim\)21.02 dB with \(L\) = 64 and 32, respectively. This shows the significance of the large \(L\) in the system. Figure 11: Throughput performance comparison under perfect SIC with no HWD across various pairing schemes at \(L=16\). Based on PA factors in (38) and (39), the maximum SSE of the system is determined while satisfying the QoS requirements for each UE. The SSE is plotted under various pairing schemes for \(L=32\) using the allocated power values, as shown in Figure 13. Figure 13 clearly indicates that the SW-SW pairing achieves superior SSE performance over other pairing schemes. This enhancement is due to the diverse channel gains within each pair in the sub-frames.