Resource Allocation for Energy Harvesting-Powered D2D Communication Underlaying UAV-Assisted Networks

In this paper, we investigate the resource allocation problem for unmanned aerial vehicle (UAV)-assisted networks, where a UAV acting as an energy source provides radio frequency energy for multiple energy harvesting-powered device-to-device (D2D) pairs with much information to be transmitted. The g...

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Bibliographic Details
Published in:IEEE transactions on green communications and networking Vol. 2; no. 1; pp. 14 - 24
Main Authors: Wang, Haichao, Wang, Jinlong, Ding, Guoru, Wang, Le, Tsiftsis, Theodoros A., Sharma, Prabhat Kumar
Format: Journal Article
Language:English
Published: Piscataway IEEE 01.03.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithm design and analysis
Algorithms
Computational geometry
Computer simulation
Convex analysis
Convexity
Device-to-device
Device-to-device communication
Energy
Energy harvesting
Energy transmission
Information processing
Mixed integer
Nonlinear programming
Optimization
Relaxation method (mathematics)
Resource allocation
Resource management
Throughput
unmanned aerial vehicle
Unmanned aerial vehicles
ISSN:2473-2400, 2473-2400
Online Access:Get full text
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Summary:In this paper, we investigate the resource allocation problem for unmanned aerial vehicle (UAV)-assisted networks, where a UAV acting as an energy source provides radio frequency energy for multiple energy harvesting-powered device-to-device (D2D) pairs with much information to be transmitted. The goal is to maximize the average throughput within a time horizon while satisfying the energy causality constraint under a generalized harvest-transmit-store model, which results in a non-convex problem. By introducing the Lagrangian relaxation method, we analytically show that the behavior of all D2D pairs at each time slot is exclusive: harvesting energy or transmitting information signals. The formulated non-convex optimization problem is thus transformed into a mixed integer nonlinear programming (MINIP). We then design an efficient resource allocation algorithm to solve this MINIP, where D.C. (difference of two convex functions) programming and golden section method are combined to achieve a suboptimal solution. Furthermore, we provide an idea to reduce the computational complexity for facilitating the application in practice. Simulations are conducted to validate the effectiveness of the proposed algorithm and evaluate the system throughput performance.
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content type line 14
ISSN:2473-2400
2473-2400
DOI:10.1109/TGCN.2017.2767203