# Joint Optimization of Relay Communication Rates in Clustered Drones under Interference Conditions
## 5 Joint Optimization Scheme for Communication Rate
### Optimization of Power Allocation Factor for Cluster Drones
Figures 8-10 illustrate the action selection of three anti-interference algorithms under various interference modes. As seen from the figures, the proposed algorithm exhibits the lowest action selection uniformity under the constant frequency interference mode. This is closely related to the constant frequency interference mode, as the algorithm, after convergence, consistently selects the optimal action, which corresponds to its reward performance. In contrast, under the hybrid frequency interference mode, the action selection uniformity is the highest due to the presence of entropy, which prompts the relay drone to continuously explore new solutions to maximize entropy. Figure 8: Action selection of the BO_DSAC algorithm under different interference modes. Figure 7: Comparison of anti-interference effects with different hyperparameters. With the Conv_DQN and DQN algorithms, the action selection was relatively uniform across the three interference modes, with each action in the action space having an occurrence frequency of approximately 10%. Additionally, the Conv_DQN algorithm demonstrated better action uniformity compared to the DQN algorithm. Verification of the Joint Optimization Algorithm Effectiveness for Cluster Drone Communication Rates

The second set of experiments primarily verified the joint optimization results for the communication rates of cluster drones. To maintain generality and verify the adaptability of the algorithm proposed in this paper to different task trajectories of cluster drones, three distinct types of trajectories are set up as follows: circular, oscillatory, and complex trajectories. Their specific performances are depicted in Figure 11.

Figure 12 shows the optimization results for the total communication rate of cluster drones corresponding to the above trajectories. From the graph, it is evident that the circular trajectory has the highest total communication rate, while the oscillatory trajectory has the lowest. The total communication rate for the circular trajectory is approximately \(3.3\times 10^{7}\) bps higher than that for the complex trajectory, and the complex trajectory's rate is

Figure 10: Action selection of the DQN algorithm under different interference modes. Figure 9: Action selection of the Conv_DQN algorithm under different interference modes. about \(1\times 10^{9}\) bps higher than that for the oscillatory trajectory. The total communication rates for all trajectories have been effectively jointly optimized and, ultimately, maintained stability. Figure 11: Different motion trajectories of the cluster drones. Figure 4:0 Joint optimization for different trajectories. To verify the optimization effectiveness of the joint optimization proposal presented in this paper, a circular trajectory is used for the motion of the cluster drones, and it is compared with three other optimization schemes. The first scheme optimizes the relay drone's trajectory, transmission power, and power allocation of cluster drones. The second scheme focuses on optimizing the relay drone's trajectory, modulation, and power allocation for cluster drones, while the third optimizes the relay drone's modulation, transmission power, and power allocation for cluster drones. According to the results depicted in Figure 13, the joint optimization scheme outperformed the others, improving the communication rate by \(1.2932\times 10^{11}\) bps, which represents 47.68% of the total optimized communication rate. Moreover, the system achieves stability after the fourth round of optimization iterations, showing good convergence. Communication delay is primarily composed of propagation delay and transmission delay. Propagation delay is calculated on the basis of the transmission distance and propagation speed, whereas the transmission delay is related to the amount of data to be transmitted and the communication rate. In this study, since all optimization schemes are conducted under the same task context, the propagation delay is identical for different schemes.