## 4 Simulation and Discussion
However, at a high SNR, the optimized secrecy rate eventually saturates, indicating the effectiveness of the proposed scheme in mitigating information leakage even in the presence of multiple eavesdroppers. Interestingly, this saturation suggests that the algorithm is nearing the optimal operating point, where increasing the SNR no longer provides substantial benefits in terms of secrecy rate improvement. Thus, while a high SNR is crucial for system performance, it does not lead to unlimited improvement in secrecy, implying that a careful balance of parameters is required. Figures 6 and 7 demonstrate the performance of the proposed algorithm under the Rician, Kronecker, SV, and CDL channel models. Similar to the results under the LOS channel, the optimization performance of the proposed algorithm significantly outperforms the baseline algorithms. Whether in the rich scattering Rician channel or the Kronecker channel with channel correlation, the proposed algorithm consistently delivers a substantial improvement in the system's secrecy rate. This indicates that the proposed multi-beam optimization and power allocation strategy effectively suppresses the eavesdropper's reception capability while ensuring the communication quality for the legitimate receiver across different channel environments. From the simulation results, although the secrecy rate in complex channel models (such as the Rician and Kronecker channels) is impacted by multipath interference, the proposed algorithm still maintains its advantage over traditional methods. In the SV and CDL channels, despite the additional challenges introduced by multipath propagation, the proposed precoding optimization strategy effectively handles interference suppression and maintains high security performance. In conclusion, regardless of the channel model, the proposed algorithm demonstrates strong advantages in enhancing physical-layer security and can adapt to dynamic variations in different propagation environments. In Figures 8 and 9, we analyze the performance of the proposed algorithm under the scenario of a moving UAV, considering processing delay and angular estimation errors. In Figure 8, the UAV height is set to \(h=100\) m and the speed is \(v=40\) m/s. The curves show the secrecy rate performance under different SNRs with a processing delay. As the SNR increases, the impact of processing delay on secrecy rate becomes more significant. At higher SNRs, the impact of processing delay is amplified because the UAV's position and angle estimates are increasingly sensitive to delay, leading to greater angular inaccuracies for both [PERSON] and [PERSON]. This results in a decline in the secrecy rate. The increase in processing delay results in increasingly inaccurate angular information for [PERSON] and [PERSON], leading to a decline in the secrecy rate. Therefore, the processing delay should be minimized to improve security. In Figure 9, we present the secrecy rate when there are estimation biases in the arrival angles of [PERSON] and [PERSON], assuming positive biases for both. Again, the secrecy rate is more sensitive to errors under high SNRs. Under higher SNR conditions, even small biases in the angle estimates lead to significant performance degradation, as the accuracy of angle information directly influences the alignment of the beams and the power distribution across the system. Additionally, the results indicate that the relative bias in [PERSON] and [PERSON]'s angle information significantly impacts the secrecy rate. This further suggests that the accuracy of the relative positions of [PERSON] and [PERSON], as obtained by UAV Alice, has a greater effect on the secrecy rate than the absolute angular information. Therefore, ensuring that Alice accurately measures the relative angles between [PERSON] and [PERSON] becomes critical. This information should be continuously updated to mitigate the effects of angular errors. Figure 7: The secrecy rate of AN-GSDM under different channel models: SV channel with ULA and CDL channel.