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Wanmei Feng

Researcher at South China University of Technology

Publications -  18
Citations -  272

Wanmei Feng is an academic researcher from South China University of Technology. The author has contributed to research in topics: Transmitter power output & Wireless network. The author has an hindex of 5, co-authored 14 publications receiving 67 citations.

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UAV-Enabled SWIPT in IoT Networks for Emergency Communications

TL;DR: An emergency communications framework of UAV-enabled SWIPT for IoT networks is established, where the disaster scenarios are classified into three cases, namely, dense areas, wide areas and emergency areas, and a dynamic path planning scheme is established to improve the energy efficiency of the system.
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Joint 3D Trajectory Design and Time Allocation for UAV-Enabled Wireless Power Transfer Networks

TL;DR: A low-complexity iterative algorithm is proposed to decompose the original problem into four sub-problems in order to optimize the variables sequentially, and reformulated as a single-variable optimization problem where charging time is the optimization variable, and can be solved using the standard convex optimization techniques.
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Joint 3D Trajectory and Power Optimization for UAV-Aided mmWave MIMO-NOMA Networks

TL;DR: In this article, a UAV-aided mmWave NOMA system is considered, where a single UAV serves as a flying base station (BS) to provide wireless access services to a set of IoT devices in different clusters.
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NOMA-based UAV-aided networks for emergency communications

TL;DR: An emergency communications framework of NOMA-based UAV-aided networks is established, where the disasters scenarios can be divided into three broad categories that have named emergency areas, wide areas and dense areas and a joint UAV deployment and resource allocation scheme is developed to extend the UAV coverage for IoT devices in wide areas.
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Hybrid Beamforming Design and Resource Allocation for UAV-Aided Wireless-Powered Mobile Edge Computing Networks With NOMA

TL;DR: By applying the polyhedral annexation method and the deep deterministic policy gradient (DDPG) algorithm, an effective algorithm is developed to derive the closed-form solution for the optimal 3D deployment of the UAV, and a solution is found for the hybrid beamformer.