EURASIP Journal on Wireless Communications and Networking (May 2021)
Performance analysis of the collaborative caching strategy in an UAV-RAN
Abstract
Abstract Ultra-reliable and low-latency communication (URLLC) is one of the main service categories in the fifth-generation communication systems, which lays the foundation for emerging data-exploring video applications with strict end-to-end latency requirement. Unmanned aerial vehicle (UAV) enabled radio access network (UAV-RAN) is an effective architecture to improve the wireless coverage. Combining wireless caching with UAV-RAN is one of the key driving forces to reduce the burden of wireless traffic, provide resilient coverage and reduce the delay in heterogeneous URLLC networks. In this paper, a collaborative caching strategy is proposed for UAV-RANs. First, a scalable video coding (SVC)-based video library is presented to provide users with videos of different perceptual qualities, and the popularity of different definition videos is also analyzed. Then, we propose a heterogeneous network where UAVs within a distance from based station (BS) can be provided with error-free data and UAVs at several stop points can provide data service to users while BS can offer all users data service. Next, an SVC-based two-tier cooperative caching model is proposed, where BS and UAVs store different video encoded files on the basis of caching matrix. Finally, the energy consumption of UAV and the caching hit probability (CHPro) are analyzed, and the optimal caching matrix is obtained via the maximization of CHPro. The maximization problem is proved to be NP hard, and we propose a two-step solution based on the simulated annealing algorithm. Considering URLLC, the average service delay is also analyzed and proved that the proposed strategy is efficient in reducing delay. Simulation results demonstrate that the collaborative caching strategy is more suitable for the UAV-RANs with a skew video popularity library and an ultra-dense user distribution. Compared with other contrasting schemes, the proposed collaborative caching strategy can achieve quasi-optimal performance.
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