Drone-Small-Cell-Assisted Spectrum Management for 5G and Beyond Vehicular Networks

被引:1
|
作者
Shen, Hang [1 ]
Heng, Yilong [1 ]
Shi, Ning [2 ]
Wang, Tianjing [1 ]
Bai, Guangwei [1 ]
机构
[1] Nanjing Tech Univ, Coll Comp Sci & Technol, Nanjing 211816, Peoples R China
[2] Nanjing Trusted Blockchain & Algorithm Econ Inst, Nanjing 211899, Peoples R China
基金
中国国家自然科学基金; 国家重点研发计划;
关键词
Vehicular networks; drone-small-cell; spectrum slicing; resource allocation; QoS-guarantee; RESOURCE-MANAGEMENT; CHALLENGES;
D O I
10.1109/ISCC55528.2022.9912871
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
With advancements in cellular vehicle-to-everything (C-V2X) and drone manufacturing technologies, integrating drone-small-cells (DSCs) into terrestrial cellular networks is a promising solution to enabling diversified vehicle applications. In this paper, a multi-DSC-assisted dynamic spectrum management framework is presented to maximize the network utility under quality-of-service (QoS) constraints in 5G and beyond cellular vehicular networks. The network utility maximization problem is formulated as mixed-integer nonlinear programming regarding association patterns between vehicles and base stations (BSs) and spectrum partitioning among heterogeneous BSs. For mathematical tractability, the joint optimization problem for spectrum partitioning and vehicle-DSC associations is transformed as a biconcave optimization problem. An alternate search algorithm is then designed to determine vehicle association patterns and spectrum slicing ratios. Our simulation demonstrates that compared with state-of-the-art methods, the proposed scheme achieves a significant performance improvement in network throughput and spectrum utilization.
引用
收藏
页数:8
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