Robust Resource Allocation Algorithm for Energy-Harvesting-Based D2D Communication Underlaying UAV-Assisted Networks

Energy efficiency (EE) is a significant performance indicator in unmanned aerial vehicle (UAV)-assisted communication networks for providing a balance between power consumption minimization and transmission rate maximization. However, most of the current works focus on the transmission rate maximiza...

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Bibliographic Details
Published in:IEEE internet of things journal Vol. 8; no. 23; pp. 17161 - 17171
Main Authors: Xu, Yongjun, Liu, Zijian, Huang, Chongwen, Yuen, Chau
Format: Journal Article
Language:English
Published: Piscataway IEEE 01.12.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Communication
Communication networks
Data communication
Device-to-device communication
Device-to-device communications
Energy harvesting
energy harvesting (EH)
Errors
Flight altitude
Internet of Things
Lagrange dual theory
Maximization
Optimization
Outages
Power consumption
Resource allocation
Resource management
robust resource allocation
Robustness
Transmission rate (communications)
Uncertainty
unmanned aerial vehicle (UAV) communications
Unmanned aerial vehicles
ISSN:2327-4662, 2327-4662
Online Access:Get full text
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Summary:Energy efficiency (EE) is a significant performance indicator in unmanned aerial vehicle (UAV)-assisted communication networks for providing a balance between power consumption minimization and transmission rate maximization. However, most of the current works focus on the transmission rate maximization under perfect channel state information (CSI) and exact coordinate information, which is too ideal in practical systems due to channel estimation errors and coordinate estimation errors. Thus, robust resource allocation algorithms with imperfect CSI and coordinate information are critically important to reduce users' outages and improve system robustness. In this article, a robust EE maximization problem with channel uncertainties and coordinate uncertainties is formulated for an energy harvesting-based device-to-device (D2D) communication underlaying UAV-assisted network under some necessary constraints, which involve the outage probability constraints of ground terminals, the flight altitude constraint of the UAV, the minimum harvested energy constraints of D2D users, and the transmission time constraint. Both radio resource allocation and the flight altitude are jointly optimized based on the worst case approach. The considered nonconvex problem is transformed into a convex one by exploiting variable relaxation and variable substitution approaches. The Lagrange dual theory is used to derive the closed-form expressions of robust resource allocation. Simulation results demonstrate the effectiveness of the proposed algorithm by comparing it with the benchmark algorithms in terms of EE and robustness.
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ISSN:2327-4662
2327-4662
DOI:10.1109/JIOT.2021.3078264