  Unmanned aerial vehicles (UAVs)-aided device-todevice (D2D) networks have
attracted great interests with the development of 5G/6G communications, while
there are several challenges about resource scheduling in UAVs-aided D2D
networks. In this work, we formulate a UAVs-aided D2D network resource
scheduling optimization problem (NetResSOP) to comprehensively consider the
number of deployed UAVs, UAV positions, UAV transmission powers, UAV flight
velocities, communication channels, and UAV-device pair assignment so as to
maximize the D2D network capacity, minimize the number of deployed UAVs, and
minimize the average energy consumption over all UAVs simultaneously. The
formulated NetResSOP is a mixed-integer programming problem (MIPP) and an
NP-hard problem, which means that it is difficult to be solved in polynomial
time. Moreover, there are trade-offs between the optimization objectives, and
hence it is also difficult to find an optimal solution that can simultaneously
make all objectives be optimal. Thus, we propose a non-dominated sorting
genetic algorithm-III with a Flexible solution dimension mechanism, a Discrete
part generation mechanism, and a UAV number adjustment mechanism (NSGA-III-FDU)
for solving the problem comprehensively. Simulation results demonstrate the
effectiveness and the stability of the proposed NSGA-III-FDU under different
scales and settings of the D2D networks.
