Building Blockage-Aided Interference Coordination for Multi-UAV-Enabled Wireless Networks

This study challenges the conventional view that wireless signal blockages are solely detrimental by exploring how non-line-of-sight (NLoS) channels can reduce co-channel interference and improve network performance. By leveraging the mobility of unmanned aerial vehicles (UAVs), this research examines the joint optimization of communication resources and UAV trajectories in multi-UAV-enabled wireless networks to maximize the minimum spectral efficiency (SE) among ground nodes (GNs) by coordinating co-channel interference. We first propose a new analytical model to identify potential signal blockages caused by multiple buildings and a novel building avoidance method that ensures safe and efficient UAV operations. To solve the problem formulated as non-convex mixed-integer nonlinear programming, we employ various optimization techniques: We first decompose the original problem into multiple convex subproblems for each optimization variable using quadratic transform and successive convex approximation. The penalty convex-concave procedure is applied to maintain the binary nature of scheduling indicators. To efficiently address signal blockage and building avoidance constraints, the separating hyperplane theorem is applied along with the approximation of the indicator function. Finally, we utilize block coordinate descent algorithm to iteratively solve the convex subproblems in sequence. The simulation results confirm that UAVs optimize their trajectories to establish LoS channels for transmitting desired signals to scheduled GNs while forming NLoS channels to mitigate interference for others. In this way, the network performance compared to baseline schemes is significantly enhanced. Furthermore, under the proposed building avoidance constraint, UAVs maintain continuous trajectories without violating building boundaries.