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- W4211167660 abstract "This article considers a wireless network consisting of unmanned aerial vehicles (UAVs), deployed as aerial base stations, and a large number of terrestrial users randomly distributed in a dense urban area. The main objective of this work is to maximize the downlink rate of users along with clustering of users and 2-D initial placement of UAVs, which effectively minimizes the clustering error. To achieve this goal, we estimate the next users’ locations with deep echo-state network (ESN) to find the movement pattern of users with high accuracy. Then, we propose the single- and multiagent actor–critic (AC) algorithms for UAVs’ initial deployment and trajectory design, where the multiagent scheme employs an efficient bandwidth allocation. Simulation results supported by a real data set of the terrestrial users’ coordinates indicate that, when the deep ESN algorithm is used, the accuracy is 93.75% for longitude and 88.36% for latitude compared to the simple ESN performance. Moreover, the use of single- and multiagent AC algorithms display better performance in terms of downlink rate and convergence speed than value-based algorithms such as deep <inline-formula xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink> <tex-math notation=LaTeX>$Q$ </tex-math></inline-formula> -network schemes." @default.
- W4211167660 created "2022-02-13" @default.
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- W4211167660 date "2022-08-15" @default.
- W4211167660 modified "2023-09-27" @default.
- W4211167660 title "Single- and Multiagent Actor–Critic for Initial UAV’s Deployment and 3-D Trajectory Design" @default.
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- W4211167660 doi "https://doi.org/10.1109/jiot.2022.3150184" @default.
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