Paper Info
Title
Maximizing Sampling Data Upload in Ambient Backscatter-Assisted Wireless-Powered Networks
Abstract
This article studies a novel problem that aims to maximize the number of uploaded samples by devices in wireless-powered Internet of Things (IoT) networks. To do so, it takes advantage of ambient backscatter communications (AmBC) to help sensor devices conserve energy, and thus leaving them with more energy to collect samples. We outline a mixed-integer linear program (MILP) that aims to determine the operation mode of each device in each time slot in order to maximize the total amount of uploaded samples. We also present a heuristic approach to set the operation mode of devices based on their residual energy and data. Our results show that as compared to the case without AmBC, the total data uploaded by devices increases by 48% and 45% for the MILP and heuristic, respectively-both of which exploit AmBC.
Year
DOI
Venue
2021
10.1109/JIOT.2021.3061087
IEEE Internet of Things Journal
Keywords
DocType
Volume
Ambient backscatter communications (AmBC),link schedule,optimization,sampling,wireless-powered networks
Journal
8
Issue
ISSN
Citations 
15
2327-4662
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
ying liu136446.92
Kwan Wu Chin22810.64
Changlin Yang3608.85