Optimal Resource Allocation in Ground Wireless Networks Supporting Unmanned Aerial Vehicle Transmissions

Cognitive UAV-Aided URLLC and mMTC Services: Analyzing Energy Efficiency and Latency

“…Hu et al (2020) suggested a UAV-enabled ground wireless network where two transmission systems, including relaying and NOMA, were proposed. In addition, they presented infinite blocklength (IBL) and finite blocklength (FBL) codes, and proposed an optimal resource allocation technique for the relaying and NOMA systems to improve the UAV throughput while maintaining the QoS for the ground user [26]. She et al (2019) presented a URLLC-enabled UAV communication scheme containing a control and non-payload communication (CNPC) channel, where they optimised the UAV height, antenna configuration, and the period of the uplink and downlink transmission state to enhance the CNPC link between the UAV and ground control station.…”

“…To tackle this problem, an FBL information theoretic model was developed in [26] - [31]. Using this model, several studies have been conducted on UAV throughput [26], available range of the CNPC link [27], decoding error probability [28], block error probability [29], and data rate [30], [31]. Only the aforementioned study [31] considered the performance of a UAV-aided CR network; however, it did not assume the NOMA system.…”

Multiple CUAV-Enabled mMTC and URLLC Services: Review of Energy Efficiency and Latency Performance

“…In the past few years, researchers have explored the various applications of UAV networks by applying IBLT and FBLT. Using the FBLT scheme, non-orthogonal multiple access (NOMA)based UAV-aided communication networks have been proposed [7]. The authors of [8] focused on the control and non-payload links of UAV communication systems.…”

“…The aforementioned studies on UAV communications [7]- [16] focused primarily on relay networks, IoT networks, D2D networks, and CR networks where the FBLT was applied. In [7], the authors investigated optimum resource allocation methods for NOMA and relaying systems to maximize UAV throughput while ensuring ground users (GUs) transmission quality in terms of throughput and reliability. In [10], the research studied jointly optimizing the UAV's position and power to decrease the probability of decoding errors while maintaining latency limitations.…”

“…To the best of the authors' knowledge, there is no recent work on the CUAV-assisted IoT network using the NOMA technique beyond [1]. In addition, the subject of maximizing energy efficiency has not been studied in the available literature [7,10,11,16]. Moreover, the UAV pairing technique in CR environment utilizing FBLT scheme has not been recently studied [17]- [20].…”