4.7 Article

Probabilistic Cache Placement in UAV-Assisted Networks With D2D Connections: Performance Analysis and Trajectory Optimization

期刊

IEEE TRANSACTIONS ON COMMUNICATIONS
卷 68, 期 10, 页码 6331-6345

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCOMM.2020.3006908

关键词

Device-to-device communication; Unmanned aerial vehicles; Trajectory; Probabilistic logic; Interference; Wireless communication; Transmitters; Probabilistic cache placement; cache hit probability; success transmission probability; trajectory optimization

资金

  1. National Natural Science Foundation of China [61701230]
  2. Natural Science Foundation of Jiangsu Province [BK20170805]
  3. Fundamental Research Funds for the Central Universities [NE2018107]
  4. Wallenberg AI, Autonomous Systems and Software Program and Nanyang Technological University (WASP/NTU) [M4082187 (4080)]
  5. Singapore MOE Tier 1 [2017-T1-002-007 RG122/17]
  6. MOE Tier 2 [MOE2014-T2-2-015 ARC4/15]
  7. Singapore EMA Energy Resilience [NRF2017EWT-EP003-041]
  8. Singapore NRF [NRF2015-NRF-ISF001-2277]

向作者/读者索取更多资源

With the exponential growth of data traffic, caching is regarded as a promising solution to combine with unmanned aerial vehicle (UAV)-assisted networks, which can offload cellular traffic and improve the system performance. Moreover, the cache capacity at user side can be leveraged, e.g., through local data storage or device-to-device (D2D) sharing. In this paper, we focus on the performance analysis and trajectory optimization of cache-enabled UAV-assisted networks with underlaid D2D communications. We consider both static and dynamic UAV deployments. For static UAV deployment, we first formulate an optimization problem to design the cache placement in order to maximize the cache hit probability. Then, the successful transfer probability (STP) and sum-rate are analyzed by using stochastic geometry, and their closed-form expressions are derived. For dynamic UAV deployment, the UAV moves over the cell and stops at several path points to serve users. To shorten the time required for the UAV to cover all users, a spiral algorithm is proposed to optimize the UAV trajectory, aiming at minimizing the number of UAV path points. Moreover, since at different locations, the UAV communication will incur different interference on D2D users, we derive the outage probability for the D2D users. Simulation results show the significant performance gain of our proposed probabilistic cache placement over existing strategies. For a given user density, we show that the optimal values for the UAV height which lead to the maximum UAV-STP and sum-rate exist.

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