Statistical analysis of adaptive rate and power control in urban FSO drone networks using RL-DQN-A2C

Computer Science

• Analysis of Variance 10%
• Correctness 10%
• Data Simulation 10%
• Deep Q-Network 100%
• Drone 100%
• Fast Convergence 10%
• Learning Framework 10%
• Optical Communication 30%
• Optimization Technique 10%
• Power Consumption 10%
• Reinforcement Learning 100%
• Smart City 30%
• Spectral Efficiency 50%
• Spectrum Efficiency 10%
• Systems Performance 10%
• Unmanned Aerial Vehicle 10%

Physics

• Free-Space Optical Communication 50%
• Mathematical Model 16%
• Optical Channel 33%
• Pointing Error 16%
• Smart City 50%
• Unmanned Aerial Vehicle (Space Vehicle) 33%