## 4 Simulation Results and Analysis
### Simulation Results
This is because, when only four users are to be selected for communication, even a total of eight users is sufficient to ensure the selection of four users with low channel correlation, thereby achieving a reasonably high sum rate. As the total number of users further increases, although the chance of selecting users with lower correlation improves, it does not result in a qualitative improvement in system performance. Moreover, as the total number of users increases, the computational complexity rises rapidly. Therefore, when only four users need to be selected, a total of eight users in the system strikes a good balance between communication efficiency and computational cost. The above simulations of the JAS-OUS algorithm are based on the assumption of perfect CSI, which is an ideal condition that does not hold in practical scenarios. In reality, channel estimation errors arise due to factors such as environmental variations and user mobility. Therefore, it is necessary to evaluate the performance of the JAS-OUS algorithm under imperfect CSI conditions. Here, the imperfect estimated channel is modeled as [28]  
\[\mathbf{\tilde{H}}=\delta\mathbf{H}+\sqrt{1-\delta^{2}}\mathbf{\Psi}, \tag{10}\]  
where \(\mathbf{\Psi}\) is a complex Gaussian noise matrix, whose elements follow the distribution \(\mathcal{CN}(0,\,1/10)\). The parameter \(\delta\in[0,1]\) is a scaling factor that characterizes the accuracy of channel estimation. A smaller \(\delta\) indicates less accurate CSI. When \(\delta=1\), the base station is assumed to have perfect CSI. As shown in Figure 6, when the SNR is low, imperfect CSI has a limited impact on the system sum rate, which remains close to the value under perfect CSI. However, as the SNR increases, the impact of imperfect CSI becomes more pronounced. For example, under the condition of \(\mathrm{SNR}=10\) dB, when \(\delta=0.95\) and \(\delta=0.90\), the system sum rate reaches \(97.2\%\) and \(93.1\%\), respectively, of the value achieved with perfect CSI. In contrast, under \(\mathrm{SNR}=30\) dB, when \(\delta=0.95\) and \(\delta=0.90\), the system sum rate drops to only \(71.9\%\) and \(62.7\%\), respectively, of that under perfect CSI. This is because under imperfect CSI, inter-user interference must be taken into account. At low SNR, the performance is dominated by channel noise, and the degradation due to interference is negligible. However, at high SNR, the impact of noise diminishes, and interference becomes the dominant limiting factor, pushing the system into an interference-limited regime. As a result, under high SNR, the  
Figure 5: Comparison of the average sum rate with various mobile user configurations. negative impact of imperfect CSI on the overall signal to interference plus noise ratio (SINR) becomes more substantial, leading to rate saturation or even degradation. Next, the JAS-PFUS algorithm for fairness scheduling purpose is simulated. In Figure 7, we compare the system throughput of the JAS-PFUS scheme for three different time slots. Both the amount of transmitting antennas and mobile users are 16, with 4 being the amount of target-selected transmitting antennas and users. It can be observed from the figure that, as the SNR increases, the sum rate of the JAS-PFUS algorithm also increases. Moreover, the impact of the number of time slots \(T_{c}\) on the system sum rate is negligible. This is because the window is simply a time-scale parameter that controls the statistical averaging of the transmission rate. As long as each user's average rate reflects its long-term trend, the statistical characteristics of the system scheduling remain stable, and thus the system weighted sum rate shows little variation. However, if the number of time slots is too large, the scheduling response becomes sluggish, leading to situations where some users are not scheduled for extended periods. Conversely, if the number of time slots is too small, the system becomes biased toward users with better instantaneous channel quality, and the fairness of scheduling cannot be maintained.