The rapid advancement of 5G and 6G technologies has spurred the development of Satellite-Terrestrial Networks (STNs), integrating terrestrial infrastructure with Low Earth Orbit (LEO) satellites to enable seamless global connectivity. Efficient spectrum allocation and interference management remain major challenges due to limited resources and the dynamic behavior of satellites. This study addresses these challenges by optimizing base station (BS) deployment to enhance spectral efficiency and reduce interference in STN environments. Delaunay Triangulation (DT) is employed to establish initial spatial separation between BSs, followed by gradient descent (GD) for fine-tuned optimization. Simulation results demonstrate that the optimized scenario substantially reduces interference and improves key performance metrics, including SINR, INR, CI Ratio, and received power, with gains ranging from 30% to 400%. These findings, derived from small-scale simulations, indicate the framework’s potential for enhancing STN performance in dense and interference-prone environments and provide a foundation for future research on interference-resilient STN architectures.

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Optimizing Base Station Placement to Minimize Interference for Satellite Terrestrial Networks (STN)

  • Zakiyyah Samath Fathima,
  • Bhargavi Goswami,
  • Manasa Kulkarni,
  • Muhammad Furqan,
  • Joy Paulose

摘要

The rapid advancement of 5G and 6G technologies has spurred the development of Satellite-Terrestrial Networks (STNs), integrating terrestrial infrastructure with Low Earth Orbit (LEO) satellites to enable seamless global connectivity. Efficient spectrum allocation and interference management remain major challenges due to limited resources and the dynamic behavior of satellites. This study addresses these challenges by optimizing base station (BS) deployment to enhance spectral efficiency and reduce interference in STN environments. Delaunay Triangulation (DT) is employed to establish initial spatial separation between BSs, followed by gradient descent (GD) for fine-tuned optimization. Simulation results demonstrate that the optimized scenario substantially reduces interference and improves key performance metrics, including SINR, INR, CI Ratio, and received power, with gains ranging from 30% to 400%. These findings, derived from small-scale simulations, indicate the framework’s potential for enhancing STN performance in dense and interference-prone environments and provide a foundation for future research on interference-resilient STN architectures.