A UAV-Enabled Wireless Powered Sensor Network Based on NOMA and Cooperative Relaying With Altitude Optimization

Shen, Tianji; Ochiai, Hideki

doi:10.1109/ojcoms.2020.3042257

Cited by 20 publications

(8 citation statements)

References 49 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This sensor data are often offloaded to a UAV for processing so that the UAV can facilitate coordination and optimal driving decisions among vehicles. Therefore, the UAV must be capable of collecting, storing, mining, analyzing, and processing data with minimum delay [5]. Furthermore, in UAV-assisted C-V2X communication, vehicle speed and density change continuously over time and location.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Unmanned Aerial Vehicle-Assisted Cellular Vehicle-to-Everything Communication Using Markovian Game in a Federated Learning Environment

Fernando,

Gupta

2024

Drones

View full text Add to dashboard Cite

The paper studies a game theory model to ensure fairness and improve the communication efficiency in an unmanned aerial vehicle (UAV)-assisted cellular vehicle-to-everything (C-V2X) communication network using Markovian game theory in a federated learning (FL) environment. The UAV and each vehicle in a cluster utilized a strategy-based mechanism to maximize their model completion and transmission probability. We modeled a two-stage zero sum Markovian game with incomplete information to jointly study the utility maximization of the participating vehicles and the UAV in the FL environment. We modeled the aggregating process at the UAV as a mixed strategy game between the UAV and each vehicle. By employing Nash equilibrium, the UAV determined the probability of sufficient updates received from each vehicle. We analyzed and proposed decision-making strategies for several representative interactions involving gross data offloading and federated learning. When multiple vehicles enter a parameter transmission conflict, various strategy combinations are evaluated to decide which vehicles transmit their data to the UAV. The optimal payoff in a transmission window is derived using the Karush–Khun–Tucker (KKT) optimality conditions. We also studied the variation in optimal model parameter transmission probability, average packet delay, UAV transmit power, and the UAV–Vehicle optimal communication probabilities under different conditions.

show abstract

Section: Introductionmentioning

confidence: 99%

Analysis of Unmanned Aerial Vehicle-Assisted Cellular Vehicle-to-Everything Communication Using Markovian Game in a Federated Learning Environment

Fernando,

Gupta

2024

Drones

View full text Add to dashboard Cite

show abstract

“…Over the past decade, unmanned aerial vehicles (UAVs), with their advantages of high mobility, low cost, and rapid deployment, have been used in diverse applications, including surveillance, rescue, cargo transport, and data collection in wireless sensor networks [1,2]. The research community is highly interested in the newest emerging application of UAVs, that is, UAV-assisted wireless communication (UAVWC).…”

Section: Introductionmentioning

confidence: 99%

“…Furthermore, UAVs have gained extensive utilization within wireless sensor networks. As mobile access points or base stations, UAVs present a promising resolution to address the substantial storage demands prevalent in wireless sensor networks [2,7]. By facilitating UAV-assisted data aggregation from numerous sensor nodes equipped with wireless capabilities, the singular-antenna UAV empowers all sensor nodes within its coverage scope to transmit data.…”

Section: Introductionmentioning

confidence: 99%

UAV-Assisted Cooperative NOMA and OFDM Communication Systems: Analysis and Optimization

Kieu-Xuan,

Le-Thi

2024

JSAN

View full text Add to dashboard Cite

Utilizing unmanned aerial vehicles (UAVs) to facilitate wireless communication has emerged as a viable and promising strategy to enhance current and prospective wireless systems. This approach offers many advantages by establishing line-of-sight connections, optimizing operational efficiency, and enabling flexible deployment capabilities in various terrains. Thus, in this paper, we investigate UAV communication in a relaying network in which a UAV helps communication between a source and two destination users while flying to a location. To have a complete view of our proposed system, we consider both orthogonal multiple access, such as OFDMs and non-orthogonal multiple access (NOMA) scenarios. Moreover, we apply successive convex optimization (SCO) and the block-coordinate gradient descent (BCGD) for the sum-rate optimization problems to improve the system performance under constraints of total bandwidth and total power at the ground base station and UAV. The experimental results validate that the achievable secrecy rates are notably enhanced using our proposed algorithms and show optimal trends for critical parameters, such as transmit powers, the flight trajectory and speed of the UAV, and resource allocation of OFDM and NOMA.

show abstract

“…WPCN technology can help energy-constrained nodes obtain energy from other nodes or the surrounding environment, and utilize this energy to transmit information to other nodes. WPCN has been widely used in wireless sensor networks (WSNs) [9], Internet of Things (IoT) systems [10], Unmanned Aerial Vehicle (UAV) communications [11], mobile edge computing (MEC) [12] and other fields. In recent years, WPCN technology has attracted extensive attention in academic circles.…”

Section: Introductionmentioning

confidence: 99%

Nonlinear Energy Harvesting and Clustering Cooperation in WPCNs

Yuan

Zhang

Liang

et al. 2023

Wireless Pers Commun

View full text Add to dashboard Cite

The increasing demand for data and the rapid increase in the number of wireless connected devices make the shortage of energy and spectrum resources more serious. This paper considers a wireless powered communication network (WPCN) composed of N wireless devices (WDs) installed with single-antenna and a hybrid access point (HAP) equipped with multi-antenna, where HAP sends wireless energy to WDs in the downlink and receives information transmission from WDs in the uplink. To overcome "double near and far" problem, this paper adopts a clustering cooperative transmission method to enhance some WDs' throughput performance far from the HAP, i.e., one of N WDs is selected as a cluster head (CH) and the remaining (N − 1) WDs as cluster members (CMs), and the CH helps relay CMs' information to transmit. However, because the CH needs to transmit N WDs' information, its energy consumed during information transmission will be the bottleneck of the system performance. To achieve a tradeoff between energy and data rate, this paper adopts multi-antenna energy beamforming technology to concentrate more energy to transmit the CH, so as to balance the energy consumption among all WDs. Considering the influence of in-phase/orthogonal imbalance,nonlinear amplification amplitude and phase noise on those physical transceivers of low-cost sensor nodes, nonlinear energy harvesting technology is employed to improve throughput performance of the WPCN system. Particularly, the proposed scheme's throughput performance is derived, and simulation results demonstrate that this scheme can be effective to increase the WPCN system's throughput fairness and spectral efficiency.

show abstract

A UAV-Enabled Wireless Powered Sensor Network Based on NOMA and Cooperative Relaying With Altitude Optimization

Cited by 20 publications

References 49 publications

Analysis of Unmanned Aerial Vehicle-Assisted Cellular Vehicle-to-Everything Communication Using Markovian Game in a Federated Learning Environment

Analysis of Unmanned Aerial Vehicle-Assisted Cellular Vehicle-to-Everything Communication Using Markovian Game in a Federated Learning Environment

UAV-Assisted Cooperative NOMA and OFDM Communication Systems: Analysis and Optimization

Nonlinear Energy Harvesting and Clustering Cooperation in WPCNs

Contact Info

Product

Resources

About