Multi-UAV Assisted IoT NOMA Uplink Communication System for Disaster Scenario

Abstract

Unmanned aerial vehicle (UAV) communication has become a prominent technology that can effectively assist in IoT systems. The inherent features of UAV such as mobility, flexibility, and fast deployment make it preferable for emergency Internet of Things (IoT) applications. In this paper, we consider a multi-UAV assisted wireless network to support uplink communication for IoT devices distributed over a disaster area. The network involves two types of UAVs: sector UAV (SU) and anchor UAV (AU). The SU hovers at a fixed height over the sector around the temporary base station (TBS), collects the information from the respective IoT devices and relays them to the TBS via AU. The AU revolves continuously around the TBS and relays the information between the SUs and TBS periodically. We aim to improve the uplink capacity of the system. To achieve this, we employ non-orthogonal multiple access (NOMA), where we jointly optimize the positions of SUs and the power control of IoT devices. We propose a two-step approach to solve this. First, we optimize the position of SU in each sector by minimizing the sum distances of SU from the respective IoT devices. Then, by considering the optimal SU location, we optimize the transmit power of IoT devices using Lagrange dual method. Finally, the experimental results show that the proposed scheme improves the system capacity by 22% compared to the state-of-the-art schemes.INDEX TERMS UAV network, Internet-of-Things, uplink transmission, NOMA, system capacity.

Complementarity, Interoperability, and Level of Integration of Humanitarian Drones with Emerging Digital Technologies: A State-of-the-Art Systematic Literature Review of Mathematical Models

“…However, many researchers have assumed a stationary node, even if the target is a user device, i.e., an inherently mobile node, because its speed is naturally much slower than that of a UAV. In the communication between a UAV and stationary sensors [111,120,121,131,138,143,148,151,153,157,158,162,[166][167][168][169][170][171][172][173], the sensing area is divided into clusters and sensing nodes into cluster members, cluster heads, and relay nodes, responsible for data sensing, collection, and forwarding, respectively [172]. Clustering can reduce energy consumption, increase network scalability, extend battery life, decrease network delay, and boost throughput [174,175].…”

“…In [134], the hovering region was enhanced through a tether, ensuring longer flight times. Six nonorthogonal multiple access (NOMA) schemes have been proposed by the authors in our sample, with the aim of minimizing the transmitting power of users and mobile devices [126] as well as maximizing the achievable rate of devices [129,157,166], throughput [173], and energy efficiency [130]. Researchers [127,128] have targeted the maximization of the number of connected mobile devices by extending network coverage.…”

Unmanned Aerial Vehicle Communications for Civil Applications: A Review

“…The authors suggested that path aggregation networks (PANet) show promise in real-time applications when solving nonconvex problems associated with optimal 3D placement in communication networks. A Multi-UAV assisted NOMA wireless network uplink communication for IoT devices is proposed by Barick and Singhal for disaster scenarios [345]. NOMA allows the improvement of the uplink capacity of the system by jointly optimizing the position of the UAVs and the power control of the IoT devices.…”

ECMS: Energy-Efficient Collaborative Multi-UAV Surveillance System for Inaccessible Regions

“…[14] proposes a mathematical model to find the inter UAV distances in a multi-UAV network to maximize the coverage. In [15], the authors consider a network topology for monitoring a post-disaster scenario. This gives a mathematical model to decide the optimal UAV positions for providing coverage with minimum transmitting power.…”