Integrating Base Station with Intelligent Surface for 6G Wireless Networks: Architectures, Design Issues, and Future Directions
Yuwei Huang, Lipeng Zhu, and Rui Zhang

TL;DR
This paper explores the integration of intelligent surfaces with base stations in 6G wireless networks, discussing architectures, design challenges, and future research directions to improve coverage and efficiency.
Contribution
It provides a comprehensive overview of IS-integrated base station architectures, design issues, and performance comparisons with conventional setups.
Findings
IS integration enhances network throughput and coverage
Numerical results compare different IS-BS architectures
Future research directions are identified
Abstract
Intelligent surface (IS) is envisioned as a promising technology for the sixth-generation (6G) wireless networks, which can effectively reconfigure the wireless propagation environment via dynamically controllable signal reflection/transmission. In particular, integrating passive intelligent surface (IS) into the base station (BS) is a novel solution to enhance the wireless network throughput and coverage both cost-effectively and energyefficiently. In this article, we provide an overview of IS-integrated BSs for wireless networks, including their motivations, practical architectures, and main design issues. Moreover, numerical results are presented to compare the performance of different IS-integrated BS architectures as well as the conventional BS without IS. Finally, promising directions are pointed out to stimulate future research on IS-BS/terminal integration in wireless networks.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsSatellite Communication Systems · Advanced Wireless Communication Technologies · Antenna Design and Analysis
MethodsBalanced Selection
