STAR-RIS Assisted Train-to-Ground Communications in Space-Air-Ground Integrated Networks
In the space-air-ground integrated network (SAGIN), high-speed railway (HSR) communication is expected to be enhanced by simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RIS). However, when both aerial platforms and ground base stations (BSs) provide services to HSR user equipments (UEs), severe signal interference can arise, leading to the system failing to meet the quality of service (QoS) requirements of the flows. In this paper, we introduce the optimization problem of transmission scheduling for STAR-RIS assisted train-to-ground communications in SAGIN. To address this issue, a phase optimization algorithm of passive STAR-RIS is proposed to improve the channel quality of HSR UEs. Furthermore, a coalition game algorithm is proposed to associate HSR UEs with the optimal links that minimize inter-flow interference. Finally, a QoS-aware flow scheduling algorithm is proposed to optimize the order of the flows for the selected links. Simulation results confirm that the proposed scheduling scheme effectively increases the number of completed flows and total transmitted bits for STAR-RIS assisted train-to-ground communications in SAGIN, outperforming traditional methods.
Authors
- Yong Niu (ORCID: https://orcid.org/0000-0002-7278-5527)
- Lei Xiong (ORCID: https://orcid.org/0000-0002-8234-6667)
- Zhangfeng Ma (ORCID: https://orcid.org/0000-0002-9068-4770)
- Zhu Han
- Ning Wang (ORCID: https://orcid.org/0000-0001-9403-3417)
- Bo Ai (ORCID: https://orcid.org/0000-0001-6850-0595)
- Lei Liu (ORCID: https://orcid.org/0009-0005-9457-683X)
Institutions
- Shaoyang University (CN)
- Beijing Jiaotong University (CN)
- Zhengzhou University (CN)
- University of Houston (US)
Publication Details
- Journal
- IEEE Transactions on Communications
- Published
- 2025-05-26
- DOI
- https://doi.org/10.1109/tcomm.2025.3573456
- Citations
- 3
- Primary Topic
- Satellite Communication Systems
- Type
- article
- Field-Weighted Citation Impact
- 14.98