Delay Optimization Design for Multi-UAVs Mobile Edge Computing Systems Based on MIMO

ZOU Yikun; WANG Gang; WANG Jinlong; LIU Haoyang

doi:10.11999/JEIT211360

Volume 44 Issue 3

Mar. 2022

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Article Navigation > Journal of Electronics & Information Technology > 2022 > 44(3): 881-889

ZOU Yikun, WANG Gang, WANG Jinlong, LIU Haoyang. Delay Optimization Design for Multi-UAVs Mobile Edge Computing Systems Based on MIMO[J]. Journal of Electronics & Information Technology, 2022, 44(3): 881-889. doi: 10.11999/JEIT211360

Citation:

ZOU Yikun, WANG Gang, WANG Jinlong, LIU Haoyang. Delay Optimization Design for Multi-UAVs Mobile Edge Computing Systems Based on MIMO[J]. Journal of Electronics & Information Technology, 2022, 44(3): 881-889. doi: 10.11999/JEIT211360

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Delay Optimization Design for Multi-UAVs Mobile Edge Computing Systems Based on MIMO

doi: 10.11999/JEIT211360

School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin 150001, China

Funds: The National Natural Science Foundation of China (62071146, 62071147)

Received Date: 2021-11-30
Accepted Date: 2022-02-26
Rev Recd Date: 2022-02-25

Available Online: 2022-03-01

Publish Date: 2022-03-28

Abstract

Abstract

The rapid growth of data and the computing limitations of devices have spawned Mobile Edge Computing (MEC) solutions in Internet of Things. Among them, the high maneuverability, easy deployment and low cost of the Unmanned Aerial Vehicle (UAV) swarm and Multiple Input Multiple Output (MIMO) technology can enhance the transmission capacity and shorten the transmission delay in the MEC network. In this paper, the maximum total delay of the system are minimized by jointly optimizing the UAV trajectory, ground users’ratio of data offloaded, assisted UAV’s ratio of data offloaded and assisted UAV’sratio of data allocation in the multi-UAVs MIMO-MEC system, in which successive convex optimization technology and block coordinate descent method are used to solve the non-convex problem. The factors affecting the system delay are discussed, and the effectiveness and convergence of the algorithm is verified in the simulation results.
- UAV communication,
- Mobile Edge Computing (MEC),
- MIMO,
- Trajectory optimization

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References(15)

References

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