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However, previous works on NOMA are mainly focused on the improvement of sum data rates. Energy efficiency resource allocation is also an important problem due to the high energy consumption by wireless communication.
As we discussed above, previous published works pay more attention on the sum data rate improvement in NOMA systems. However, for energy-efficient resource allocation problems, the technical literature is rather poor. Additionally, game theory is an advantageous tool for resource allocation problems. To the best of our knowledge, super-modular game has never been applied before on to allocate resources on NOMA systems.
摘自: Liu G , Wang R , Zhang H , et al. Super-Modular Game Based User Scheduling and Power Allocation for Energy-Efficient NOMA Network[J]. IEEE Transactions on Wireless Communications, 2018:1-1.

Unlike most of the previous works which typically treat UAVs as relays or BSs, in our work the UAVs that relay the data from other UAVs also have their own sensing tasks, i.e. we consider the UAVs as flying mobile terminals in the UAV sensing network.
摘自: Zhang S , Zhang H , Di B , et al. Cellular UAV-to-X Communications: Design and Optimization for Multi-UAV Networks[J]. IEEE Transactions on Wireless Communications, 2018, PP(99).

Nevertheless, the decentralized trajectory design problem remains to be lack of discussion. This is important since in practical scenarios the UAVs may belong to different entities, and thus they have the incentive to maximize their own utilities.
To tackle these problems, in this paper, we consider the scenario where multiple UAVs in a cellular network perform different real-time sensing tasks.
摘自 Hu J , Zhang H , Song L . Reinforcement Learning for Decentralized Trajectory Design in Cellular UAV Networks With Sense-and-Send Protocol[J]. Internet of Things Journal, IEEE, 2019, 6(4):6177-6189.

A very important question about the aerial wireless networks, which has not been addressed yet in the literature, is to find the minimum number of drone-BSs along with their placement in order to provide coverage to a set of users with some target Quality-of-Service (QoS).

摘自 Kalantari E , Yanikomeroglu H , Yongacoglu A . On the Number and 3D Placement of Drone Base Stations in Wireless Cellular Networks[C]// 2016 IEEE 84th Vehicular Technology Conference (VTC-Fall). IEEE, 2017.