This paper proposes a novel integrated aerial-terrestrial multi-operator network in which each operator deploys a number of unmanned aerial vehicle-base stations (UAV-BSs) besides the terrestrial macro base station (MBS), where each BS reuses the operator’s licensed band to provide downlink connectivity for UAV-user equipment (UAV-UE). In addition, the operators allow the UAV-UE, whose demand cannot be satisfied by the licensed band, to compete with others to obtain bandwidth resources from the unlicensed spectrum. Considering inter-cell and inter-operator interference in the licensed and unlicensed spectrum, the user association, power allocation, and dynamic spectrum sharing are jointly optimized to maximize the network throughput while ensuring the UAV-UEs’ data rate requirements. The formulated optimization problem, which is an NP-hard problem, is divided into two sequential subproblems. We propose a distributed iterative algorithm composed of a matching game, coalition game, and successive convex approximation technique to jointly solve the user association and power control subproblems in the licensed spectrum. Afterwards, we propose a three-layer auction framework to allocate the unlicensed spectrum dynamically between operators. Simulation results show that the proposed algorithms with the additional use of the unlicensed spectrum achieve 86.8% higher system throughput than that of only using the licensed spectrum.

In this paper, we investigate the resource and interference management problem in a novel scenario where multiple unmanned aerial vehicle base stations (UAV-BSs) provide cellular services to UAV users (UAV-UEs) by reusing both licensed and unlicensed spectrum. Considering the co-existence of terrestrial cellular, WiFi and UAV-BSs, a joint optimization problem is formulated for both subchannel allocation and power control of UAV-UEs over the licensed/unlicensed spectrum in order to maximize the uplink sum-rate of the multi-cell UAV-cellular network. Since the formulated problem is NP-hard, we decompose it into three sub-problems. Specifically, we first use the convex optimization and the Hungarian algorithm to obtain the global optimal of power and subchannel allocations in the licensed spectrum, respectively. Then, we propose a matching game with externalities and coalition game algorithms to obtain the Nash stable of the subchannel allocation in the unlicensed band. Local optimal power assignment in the unlicensed spectrum is obtained using the successive convex approximation (SCA) method. An iterative algorithm is thereby developed to solve the three sub-problems sequentially till reaching convergence. Simulation results show that the proposed algorithm can improve the network capacity by nearly two times than the Long Term Evolution-Advanced (LTE-A).