D2D Communications Underlaying Wireless Powered Communication Networks

In this correspondence paper, we investigate the resource allocation problem for D2D communications underlaying wireless powered communication networks, where multiple D2D pairs harvest energy from a power station equipped with multiple antennas and then transmit information signals simultaneously o...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on vehicular technology Jg. 67; H. 8; S. 7872 - 7876
Hauptverfasser: Wang, Haichao, Wang, Jinlong, Ding, Guoru, Han, Zhu
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.08.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Communication networks
Communications networks
Convex functions
D.C. programming
Device-to-device communication
device-to-device communications
Energy harvesting
Energy transmission
fractional programming
Iterative methods
Mathematical programming
Nonlinear programming
Optimization
Power control
Programming
Resource allocation
Throughput
Wireless communication
Wireless communications
Wireless networks
wireless powered communication networks
ISSN:0018-9545, 1939-9359
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:In this correspondence paper, we investigate the resource allocation problem for D2D communications underlaying wireless powered communication networks, where multiple D2D pairs harvest energy from a power station equipped with multiple antennas and then transmit information signals simultaneously over the same spectrum resource. The aim is to maximize the sum throughput via joint time scheduling and power control, while satisfying the energy causality constraints. The formulated nonconvex problem is first transformed into a nonlinear fractional programming problem with a tactful reformulation. Then, by leveraging difference of two convex functions programming, a suboptimal solution to the nonconvex problem is obtained by iteratively solving a sequence of convex problems. Simulation results demonstrate that the proposed scheme works well in different scenarios and can significantly improve the system throughput compared with the-state-of-the-art schemes.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0018-9545
1939-9359
DOI:10.1109/TVT.2018.2832068