D2D Communications Underlaying UAV-Assisted Access Networks

Unmanned aerial vehicles (UAVs)-enabled base stations (BSs) can boost the system performance of the terrestrial networks with device-to-device (D2D) communication in the scenarios that fixed BSs in the ground are not available. However, the serious interference among UAVs and multiple D2D pairs is m...

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Vydáno v:IEEE access Ročník 6; s. 46244 - 46255
Hlavní autoři: Wang, Haichao, Chen, Jin, Ding, Guoru, Wang, Shaowei
Médium: Journal Article
Jazyk:angličtina
Vydáno: Piscataway IEEE 01.01.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Algorithms
Complexity
Computational geometry
Control algorithms
Control theory
Convex analysis
Convexity
D.C. programming
Device-to-device (D2D) communications
Device-to-device communication
Gain
Hessian matrices
Interference
Networks
Optimization
Power control
Radio equipment
System performance
Throughput
Topology
unmanned aerial vehicle (UAV)
Unmanned aerial vehicles
ISSN:2169-3536, 2169-3536
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Shrnutí:Unmanned aerial vehicles (UAVs)-enabled base stations (BSs) can boost the system performance of the terrestrial networks with device-to-device (D2D) communication in the scenarios that fixed BSs in the ground are not available. However, the serious interference among UAVs and multiple D2D pairs is more challenging than the terrestrial case because UAVs are changing the networks topology frequently over time. In this paper, the power control optimization is investigated for D2D communications underlaying UAV-assisted access systems, where a UAV-enabled BS serves multiple users, and the remaining users communicate with each other with the assistance of the UAV, also referred to as D2D pairs. With the aim of throughput maximization, we need to address a non-convex optimization. To this end, difference of two convex functions (D.C.) programming is invoked to solve the formulated optimization, which can obtain suboptimal solutions. Considering the UAV's limited energy and low computational capability, we further design a low-complexity power control algorithm by exploiting the Hessian matrix's structure. Simulation results show that the proposed algorithms perform quite well for all considered scenarios. Both of them can improve the system throughput dramatically. Moreover, the low-complexity algorithm produces almost the same throughput as the D.C. programming method with much lower computation burden.
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ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2018.2865629