## 4 Simulation Results and Analysis
### Simulation Results  
First, several different non-proportional fairness user scheduling algorithms are compared. The proposed JAS-OUS is compared with joint antenna selection and channel power-based user scheduling (JAS-CPUS) [18] and joint antenna selection and semi-orthogonal user scheduling (JAS-SUS) [15]. JAS-SUS is chosen for comparison because of its superior communication efficiency, while JAS-CPUS has the advantage of extremely reduced computational complexity. Figure 2 illustrates the system sum rate achieved by various algorithms with different SNR. Four antennas are selected from sixteen transmitting antennas while four users are scheduled from sixteen users for message transmission. As shown in the figure, the overall rate of JAS-SUS approximates the sum rate of optimal exhaustive search. The proposed JAS-OUS outperforms JAS-CPUS and is close to the performance of JAS-SUS. For ease of calculation and presentation, the sum rate of JAS-SUS is used as the benchmark for comparison in the following simulations. In Figure 3, the achievable system throughput of three user scheduling algorithms with various transmitting antenna configurations is compared. The transmitting antennas range from 8 to 16, with the SNR fixed at 10 dB. From the figure, it is evident that as the number of transmitting antennas grows, the system sum rate shows a slow rising trend. When the transmitting antennas increases to a certain number, the sum rate approaches stability. \begin{table}
\begin{tabular}{c c} \hline \hline
**Parameters** & **Values** \\ \hline Element-wise distribution of channel \(\mathbf{H}\) & \(\mathbf{H}_{ij}\sim\mathcal{CN}(0,1)\) \\ \hline Channel noise \(\mathbf{n}\) & \(\mathbf{n}\sim\mathcal{CN}(\mathbf{0},\mathbf{1})\) \\ \hline Number of base station antennas \(N_{t}\) & 16 \\ \hline Number of antennas per user & 1 \\ \hline Number of RF chains \(N_{RF}\) & 4 \\ \hline Total number of users \(U\) & 16 \\ \hline Number of users to be selected \(K\) & 4 \\ \hline Scale factor in imperfect CSI \(\delta\) & 0.95 or 0.90 \\ \hline Element-wise distribution of the noise term \(\boldsymbol{\overline{\mathbf{v}}}\) in imperfect CSI & \(\boldsymbol{\overline{\mathbf{v}}}_{ij}\sim\mathcal{CN}(0,\;1/10)\) \\ \hline Number of time slots for JAS-PFUS \(T_{c}\) & 20 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Simulation parameters. Figure 4 presents the comparison with respect to the system sum rate using various selected antenna configurations. The quantity of selected antennas is matched to the quantity of allocated users, ranging from 4 to 10, with the SNR fixed at 10 dB. The system sum rate shows a growing trend with the growth in the number of selected antennas, i.e., the more users are served, the greater sum rate will be. The introduced algorithm outperforms JAS-CPUS. Figure 5 illustrates the system throughput with various mobile user configurations. The total number of users is set to range from 8 to 16. Four users are selected from the total for communication, and the SNR is fixed at 10 dB. As the number of users increases, the system sum rate exhibits a slow growth trend. Additionally, the performance gap between JAS-OUS and JAS-CPUS gradually widens, although the overall difference remains relatively small. The performance of JAS-OUS approaches saturation when the  
Figure 4: Comparison of the average sum rate with various selected antenna configurations. Figure 3: Comparison of the average sum rate with various transmitting antenna configurations. Figure 2: Comparison of the average sum rate at different SNR. number of users reaches 14, while the performance of the JAS-CPUS algorithm becomes even less sensitive to user number variations. These results indicate that the proposed JAS-OUS algorithm remains applicable even as the number of users increases. However, the system sum rate is not highly sensitive to the number of users, and the gain brought by additional users is marginal.