Energy-Saving Deployment Optimization and Resource Management for UAV-Assisted Wireless Sensor Networks With NOMA

• Published in: IEEE transactions on vehicular technology Vol. 71; no. 6; pp. 6609 - 6623
• Main Authors: Zhai, Daosen, Wang, Chen, Zhang, Ruonan, Cao, Haotong, Yu, Fei Richard
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.06.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Autonomous aerial vehicles; Computer simulation; Interference; Iterative algorithms; Iterative methods; NOMA; non-orthogonal multiple access; Optimization; Power consumption; Power control; Power management; Resource management; sensor networks; Sensors; unmanned aerial vehicle; Unmanned aerial vehicles; Wireless networks; Wireless sensor networks
• ISSN: 0018-9545; 1939-9359
• DOI: 10.1109/TVT.2022.3159681

Energy-saving techniques are vital for the battery-powered sensor devices (SDs), which affect their lifetime. In this paper, we propose an air-and-ground cooperative wireless sensor network (AGWSN), wherein several UAVs are deployed as aerial access points (AAPs) to assist the terrestrial access point (TAP) for data collecting. The positions of the AAPs can be modified to approach the cell-edge SDs, therefore reducing the energy of the SDs expended in uploading data. To fully exploit the potential of the AGWSN, we formulate a joint AAP position optimization, channel allocation, and power control problem to minimize the total power consumption of all SDs subject to their decoding threshold. To solve the formulated problem, we first analyze the optimal user pairing rule in each cell and based on the rule propose a maximum-weighted-independent-set inspired algorithm for the AAP position optimization. Then, we remodel the channel allocation problem as an interference minimization problem and devise a K-CUT based algorithm to solve it. We further propose a low-complex iterative algorithm to obtain the optimal transmission power for each SD. The performance of the proposed algorithms is evaluated via theoretical analysis and numerical simulation. Simulation results indicate that if the intracell and intercell interference are not well coordinated, the superiorities of the AGWSN cannot be developed, and its performance is even worse than the traditional terrestrial network (TTN). Cooperated with our algorithms, the AGWSN significantly outperforms the TTN in terms of total power consumption and probability of successful decoding.