Trajectory Optimization for UAV-to-Device Underlaid Cellular Networks by Mean-Field-Type Control

Hongliang Zhang, Zhu Han, H. Vincent Poor

Research output: Contribution to journalConference articlepeer-review

4 Scopus citations


In this paper, we consider a cellular Internet of UAVs with a massive number of UAVs, where the sensory data can be transmitted to the mobile devices by UAV-toDevice (U2D) communications, or to the base station (BS) by UAV-to-Network (U2N) communications. To improve the spectral efficiency, the U2D links can share the spectrum with U2N links. Since the sensing and transmission of the UAV are coupled by the trajectory, it is necessary to optimize the trajectory. Due to the underlay property, the trajectories of UAVs will have an impact on each other, which makes the trajectory optimization more challenging when the number of UAVs is large. To tackle this challenge, mean-field approximation is an efficient method to approximate the interactions among UAVs. Since the UAVs in the cellular Internet of UAVs are distinguishable, we propose a mean-field-type (MFT) control method to solve the trajectory optimization problem, where the interactions among. The simulation results verify the effectiveness of our proposed method.

Original languageEnglish (US)
Article number9322086
JournalProceedings - IEEE Global Communications Conference, GLOBECOM
StatePublished - 2020
Externally publishedYes
Event2020 IEEE Global Communications Conference, GLOBECOM 2020 - Virtual, Taipei, Taiwan, Province of China
Duration: Dec 7 2020Dec 11 2020

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Hardware and Architecture
  • Signal Processing


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