  Unmanned aerial vehicle (UAV) swarm has emerged as a promising novel paradigm
to achieve better coverage and higher capacity for future wireless network by
exploiting the more favorable line-of-sight (LoS) propagation. To reap the
potential gains of UAV swarm, the remote control signal sent by ground control
unit (GCU) is essential, whereas the control signal quality are susceptible in
practice due to the effect of the adjacent channel interference (ACI) and the
external interference (EI) from radiation sources distributed across the
region. To tackle these challenges, this paper considers priority-aware
resource coordination in a multi-UAV communication system, where multiple UAVs
are controlled by a GCU to perform certain tasks with a pre-defined trajectory.
Specifically, we maximize the minimum signal-to-interference-plus-noise ratio
(SINR) among all the UAVs by jointly optimizing channel assignment and power
allocation strategy under stringent resource availability constraints.
According to the intensity of ACI, we consider the corresponding problem in two
scenarios, i.e., Null-ACI and ACI systems. By virtue of the particular problem
structure in Null-ACI case, we first recast the formulation into an equivalent
yet more tractable form and obtain the global optimal solution via Hungarian
algorithm. For general ACI systems, we develop an efficient iterative algorithm
for its solution based on the smooth approximation and alternating optimization
methods. Extensive simulation results demonstrate that the proposed algorithms
can significantly enhance the minimum SINR among all the UAVs and adapt the
allocation of communication resources to diverse mission priority.
