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Compatible Deployment in Multiple Metasurfaces Aided Indoor Networks With Irregular Blockage

Jianghui Liu,Hongtao Zhang

Published 2025 in IEEE Transactions on Wireless Communications

ABSTRACT

The complex indoor environment makes the deployment of indoor communication networks difficult and expensive. Thanks to the emergence of intelligent surfaces (ISs), including intelligent reflecting surfaces (IRSs), intelligent transmission surfaces (ITSs), and intelligent omni-surfaces (IOSs), a new technology has been brought to indoor communications. However, due to the irregularly scattered distribution of indoor walls, it is difficult to achieve splendid indoor communications using only one kind of ISs. Moreover, most existing works do not consider the location optimization of ISs, resulting in poor performance. This paper proposes a new hybrid IRS/ITS/IOS assisted indoor communication scheme, where the cooperative multi-hop is considered and IRSs/ITSs/IOSs are optimally deployed in specific areas for enhancing the minimum signal-to-interference-plus-noise ratio. Specifically, we first consider the case of hybrid deployment of IRSs/ITSs, the blockage factors between the base station (BS)/users and IRSs/ITSs are modeled, and the multi-hop cooperative channel model is expressed as an explicit function of the phase shifts of IRSs/ITSs by matrix transformation. Furthermore, to deal with the non-convexity and the strong coupling between BS beamforming, phase shifts and positions of IRSs/ITSs, an efficient iterative algorithm is developed based on the successive convex approximation and semi-definite relaxation. Additionally, we analyze and illustrate that our proposed scheme can be extended to the case of IRSs/ITSs/IOSs hybrid deployment. Simulation results prove the advantages of the proposed scheme and show a 45.9% performance enhancement compared with the well-known graph-based deployment.

PUBLICATION RECORD

  • Publication year

    2025

  • Venue

    IEEE Transactions on Wireless Communications

  • Publication date

    2025-05-01

  • Fields of study

    Computer Science, Engineering

  • Identifiers
    DOI 10.1109/TWC.2025.3541203
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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