Collaborative Low-Altitude Air Traffic Control Under Communication Constraints in Integrated Sensing and Communication Networks

This paper investigates the low-altitude air traffic control under communication constraints in integrated sensing and communication (ISAC) networks. Small base stations (S-BSs) can perform both sensing and communication operations by sensing nearby unmanned aerial vehicles (UAVs) for low-altitude air traffic control. Meanwhile, SBSs transmit requested information to nearby user equipments (UEs) for satisfying their requirements. We formulate the control problem as a joint optimization problem of SBS sensing and communication within each scheduling period. The joint optimization problem is a mixed integer programming problem and the goal is to maximize the network sensing profit obtained from sensing UAVs by SBSs. We propose a combined relaxation and greedy-based nearest neighbor quantization algorithm to solve it efficiently. By analyzing the property of the problem, we first reformulate it as a continuous optimization problem and prove its convexity. The optimal solution of the convex optimization problem can be obtained, which is the performance upper bound of the original problem. Then we propose a greedy-based nearest neighbor quantization algorithm to refine the optimal but infeasible solution into a feasible and near-optimal solution. Simulation results show that our proposed algorithm performs close to the performance upper bound with different system parameter settings.