Sum-Rate Maximization for UAV Aided Wireless Power Transfer in Space-Air-Ground Networks

The Internet of things (IoT) has become a prominent platform which bridges diverse technologies in order to meet the ever-increasing application requirements of various industries. However, the IoT devices, especially in remote areas that lack infrastructures, are featured by the restricted energy a...

Full description

Saved in:
Bibliographic Details
Published in:IEEE access 2020, Vol.8, p.216231-216244
Main Authors: Jia, Huaiqi, Wang, Ying, Liu, Man, Chen, Yuanbin
Format: Article
Language:English
Subjects:
Algorithms
amplify-and-forward (AF)
Batteries
decode-and-forward (DF)
Information processing
Internet of Things
Iterative algorithms
Maximization
Optimization
Power control
Relays
Resource allocation
Satellites
space-air-ground (SAG)
Unmanned aerial vehicle (UAV)
Unmanned aerial vehicles
Wireless communication
Wireless networks
wireless power transfer (WPT)
Wireless power transmission
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The Internet of things (IoT) has become a prominent platform which bridges diverse technologies in order to meet the ever-increasing application requirements of various industries. However, the IoT devices, especially in remote areas that lack infrastructures, are featured by the restricted energy and pose great challenges on network access and sustainable communication. In this paper, we investigate the unmanned aerial vehicle (UAV) aided wireless power transfer under a space-air-ground (SAG) network, where the UAV is exploited as an aerial relay to assist in uploading information generated by ground nodes (GNs), and mounted with energy transmitter to deliver wireless energy for GNs. The goal is to maximize the system sum rate while satisfying the proportional rate for GNs and the sustainability of the ground network. To this end, by adopting decode and forward (DF) and amplify and forward (AF) protocols, two sum rate maximization problems are formulated via jointly optimizing power control, time allocation as well as UAV trajectory. The resource allocation problems are both nonconvex, which are difficult to solve directly. To tackle them, two near-optimal iterative algorithms are proposed by leveraging the successive convex approximation technology and the alternating optimization method. Extensive simulations are provided to demonstrate the effectiveness of the proposed algorithms and evaluate the impacts of various parameters on DF and AF relays.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2020.3040868