Energy Efficient Spectrum Sharing and Resource Allocation for 6G Air-Ground Integrated Networks
In this paper, we investigate the spectrum sharing and resource allocation scheme for air-ground integrated wireless network which consists of multiple unmanned aerial vehicles (UAVs) and a high altitude platform (HAP). We consider the UAVs are required to provide services or execute certain missions in the area that HAP owns the spectrum and other resources. Correspondingly, we propose an energy efficient spectrum sharing and resource allocation scheme so that the UAVs can flexibly utilize the radio resources within the area without degrading the quality of service (QoS) of the HAP. In the proposed scheme, we jointly optimize pricing of spectrum and transmit power to maximize the utility of both the HAP and UAVs in the considered system in an energy efficient manner. A game theoretic approach is then presented to find the spectrum sharing and resource allocation strategies for both HAP and UAVs and the problem has been addressed via convex optimization. Our extensive simulations demonstrate marked improvements in system utility, spectrum and energy efficiency, and also highlight the effectiveness of the proposed scheme.
Authors
- Jingyuan Liu (ORCID: https://orcid.org/0000-0001-7127-0911)
- Xu Zhao (ORCID: https://orcid.org/0000-0002-4694-4387)
- Ying‐Chang Liang
- Zheng Chang (ORCID: https://orcid.org/0000-0003-3766-820X)
- Tao Huang (ORCID: https://orcid.org/0000-0002-3545-1122)
- Wei Yao (ORCID: https://orcid.org/0000-0002-4054-5916)
Institutions
- University of Electronic Science and Technology of China (CN)
- China Telecom (China) (CN)
- China Telecom (CN)
Publication Details
- Journal
- IEEE Transactions on Network and Service Management
- Published
- 2025-01-09
- DOI
- https://doi.org/10.1109/tnsm.2025.3527651
- Citations
- 2
- Primary Topic
- UAV Applications and Optimization
- Type
- article
- Field-Weighted Citation Impact
- 9.99
Funders
- National Science Foundation
- National Natural Science Foundation of China