Multiobjective Precoder Design for Coexisting Wireless Energy Transfer and Information Transmission Systems

This paper studies the precoder design for coexisting wireless energy transfer (WET) and wireless information transmission (WIT) systems, where WET and WIT share the same spectrum band, and the cochannel interference generated by one system is regarded as useful rather than harmful resource for the...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEEE systems journal Jg. 14; H. 1; S. 445 - 456
Hauptverfasser: Zhang, Haiyang, Huang, Yongming, Wang, Jiaheng, Wang, Baoyun, Yang, Luxi
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.03.2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Cochannel interference
Coexisting wireless energy transfer and wireless information transmission
Communication system security
Computer simulation
Covariance
Design optimization
Information processing
Iterative algorithms
multiobjective optimization
Multiple objective analysis
Optimization
physical-layer security
precoder design
Receivers
Transmitters
Wireless communication
Wireless power transmission
Wireless sensor networks
ISSN:1932-8184, 1937-9234
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:This paper studies the precoder design for coexisting wireless energy transfer (WET) and wireless information transmission (WIT) systems, where WET and WIT share the same spectrum band, and the cochannel interference generated by one system is regarded as useful rather than harmful resource for the other system. Specifically, we address the transmit covariance design from the multiple-objective optimization perspective in order to simultaneously maximize the total harvested energy of energy receivers in WET and the secrecy rate of information receiver in WIT. To deal with the challenging multiple-objective optimization problem (MOOP), we first find the Utopia point of the MOOP. Then, we transform the original MOOP into two different single-objective optimization problems (SOOPs) via the weighted sum and the weighted Tchebycheff approaches, respectively. The two SOOPs are, however, nonconvex and nonsmooth. We further develop two iterative algorithms to tackle them, respectively. For comparison, a distributed transmit covariance design based on the Nash equilibrium is also proposed. Simulation results are finally presented to demonstrate the effectiveness of the proposed designs and illustrate the tradeoff between the total harvested energy and the secrecy rate.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1932-8184
1937-9234
DOI:10.1109/JSYST.2019.2920751