QoS-Guaranteed Multi-UAV Coverage Scheme for IoT Communications With Interference Management

Chen, Ruirui; Cheng, Wenchi; Ding, Yu; Wang, Bowen

doi:10.1109/jiot.2023.3301088

Cited by 7 publications

(1 citation statement)

References 44 publications

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“…Furthermore, drones are typically equipped with advanced sensors and communication technologies, allowing them to collect real-time environmental information and transmit it to command centers. This provides real-time and accurate data support for post-disaster rescue efforts, helping command centers better understand the situation, allocate resources, and formulate rescue plans [7][8][9][10]. The high maneuverability and multifunctionality of drones enable them to adapt to various emergency communication needs, improving the efficiency and success rate of post-disaster rescue.…”

Section: Introductionmentioning

confidence: 99%

Post-Disaster Emergency Communications Enhanced by Drones and Non-Orthogonal Multiple Access: Three-Dimensional Deployment Optimization and Spectrum Allocation

Li,

Zhu,

Huang

et al. 2024

Drones

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Integrating the relaying drone and non-orthogonal multiple access (NOMA) technique into post-disaster emergency communications (PDEComs) is a promising way to accomplish efficient network recovery. Motivated by the above, by optimizing the drone three-dimensional (3D) deployment optimization and spectrum allocation, this paper investigates a quality of service (QoS)-driven sum rate maximization problem for drone-and-NOMA-enhanced PDEComs that aims to improve the data rate of cell edge users (CEUs). Due to the non-deterministic polynomial (NP)-hard characteristics, we first decouple the formulated problem. Next, we obtain the optimal 3D deployment with the aid of a long short-term memory (LSTM)-based recurrent neural network (RNN). Then, we transform the spectrum allocation problem into an optimal matching issue, based on which the Hungarian algorithm is employed to solve it. Finally, the simulation results show that the presented scheme has a significant performance improvement in the sum rate compared with the state-of-the-art works and benchmark scheme. For instance, by adopting the NOMA technique, the sum rate can be increased by 9.72% and the needs of CEUs can be satisfied by enabling the relaying drone. Additionally, the convergence, complexity, and performance gap caused by iterative optimization are discussed and analyzed.

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Section: Introductionmentioning

confidence: 99%