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Pre-caching popular files at mobile users with the aid of device-to-device (D2D) communications can offload the data traffic to low-cost D2D links and reduce the network transmission cost. This leads to additional cache leasing cost brought by the lease of storage from mobile users. Besides, newly-emerging video-related applications also pose strict requirement on the network delay. Thus, it is of great significance to design caching strategies considering the transmission cost, the cache leasing cost and the delay. As the movement of mobile users can improve the communication opportunities among different users and increase the cache hit ratio, in this paper, mobility-aware caching strategies are designed to minimize the network cost including both the transmission cost and the cache leasing cost with the delay constraint. In specific, by characterizing the user mobility as an inter-contact model, analytical expressions of the average network cost and the average file delivery delay are derived and a cost-oriented mobility-aware caching problem is formulated. To handle this mixed integer nonlinear programming (MINLP) problem, we first relax the binary cache placement indicator as a continuous one and prove that both the average network cost and the average file delivery delay are convex. Hence, an iterative caching algorithm is proposed with the successive convex approximation method. Moreover, to lower the complexity, combinatorial optimization method is adopted. Firstly, to make the caching problem tractable, the average file delivery delay constraint is implicitly added in the cost objective function as a penalty term. Then, the reformulated objective function is proved to have the non-monotone submodular property and thus a modified low-complexity greedy caching strategy is proposed. Simulation results show that, compared with the most popular caching strategy, our proposed mobility-aware caching strategy can reduce the average cost by 46% when the user speed is high.INDEX TERMS Average file delivery delay, cache leasing cost, D2D networks, mobility-aware caching strategy.

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Unmanned aerial vehicle (UAV) communication has been deemed as a promising technology to collect data for the Internet of Things (IoT) in inaccessible areas. However, due to the limited UAV flight time, traditional UAV communication may not be competent for large-scale IoT data collection. This paper considers integrating non-orthogonal multiple access (NOMA) into UAV communication systems to collect data for large-scale IoT devices within UAV flight time. We aim to minimize the total energy consumption of IoT devices while ensuring data collection, by jointly optimizing UAV trajectory, IoT device scheduling and transmit power. The formulated problem is a mixed integer non-convex problem, which is challenging to solve in general. We propose a data collection optimization algorithm (DCOA) to solve it by applying the Generalized Benders Decomposition (GBD) and successive convex approximation (SCA) techniques. Then, a greedy algorithm (GA) is also proposed to reduce complexity by simplifying the optimization of UAV trajectory and IoT device scheduling. Finally, the numerical results demonstrate that, compared with traditional UAV communication systems, the NOMA-aided UAV system performs better in terms of data collection and lower total energy consumption of IoT devices can be achieved by DCOA. INDEX TERMS Unmanned aerial vehicle (UAV) communication, non-orthogonal multiple access (NOMA), data collection, Internet of Things (IoT), energy consumption minimization.

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