LSTM-characterized Deep Reinforcement Learning for Continuous Flight Control and Resource Allocation in UAV-assisted Sensor Network

Unmanned aerial vehicles (UAVs) can be employed to collect sensory data in remote wireless sensor networks (WSN). Due to UAV's maneuvering, scheduling a sensor device to transmit data can overflow data buffers of the unscheduled ground devices. Moreover, lossy airborne channels can result in pa...

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Detalhes bibliográficos
Autor principal: Li, Kai (author)
Outros Autores: Ni, Wei (author), Dressler, Falko (author)
Formato: article
Idioma:eng
Publicado em: 2021
Assuntos:
Unmanned aerial vehicles
Flight trajectory
Resource allocation
Deep deterministic policy gradient
Long short-term memory
Experimental datasets
Texto completo:http://hdl.handle.net/10400.22/18346
País:Portugal
Oai:oai:recipp.ipp.pt:10400.22/18346

Texto Completo

http://hdl.handle.net/10400.22/18346

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