The Space-Terrestrial Integrated Network(STIN)is considered to be a promising paradigm for realizing worldwide wireless connectivity in sixth-Generation(6G)wireless communication systems.Unfortunately,excessive interf...The Space-Terrestrial Integrated Network(STIN)is considered to be a promising paradigm for realizing worldwide wireless connectivity in sixth-Generation(6G)wireless communication systems.Unfortunately,excessive interference in the STIN degrades the wireless links and leads to poor performance,which is a bottleneck that prevents its commercial deployment.In this article,the crucial features and challenges of STIN-based interference are comprehensively investigated,and some candidate solutions for Interference Management(IM)are summarized.As traditional IM techniques are designed for single-application scenarios or specific types of interference,they cannot meet the requirements of the STIN architecture.To address this issue,we propose a self-adaptation IM method that reaps the potential benefits of STIN and is applicable to both rural and urban areas.A number of open issues and potential challenges for IM are discussed,which provide insights regarding future research directions related to STIN.展开更多
基金This work was supported in part by the National Key R&D Program of China(No.2020YFB1806703)the National Natural Science Foundation of China(No.61901315)+1 种基金the State Major Science and Technology Special Project(No.2018ZX03001023)the Fundamental Research Funds for the Central Universities(No.2020RC03).
文摘The Space-Terrestrial Integrated Network(STIN)is considered to be a promising paradigm for realizing worldwide wireless connectivity in sixth-Generation(6G)wireless communication systems.Unfortunately,excessive interference in the STIN degrades the wireless links and leads to poor performance,which is a bottleneck that prevents its commercial deployment.In this article,the crucial features and challenges of STIN-based interference are comprehensively investigated,and some candidate solutions for Interference Management(IM)are summarized.As traditional IM techniques are designed for single-application scenarios or specific types of interference,they cannot meet the requirements of the STIN architecture.To address this issue,we propose a self-adaptation IM method that reaps the potential benefits of STIN and is applicable to both rural and urban areas.A number of open issues and potential challenges for IM are discussed,which provide insights regarding future research directions related to STIN.
