In the design of a metasurface-assisted system for indoor environments, it is essential to take into account not only the performance gains and coverage extension provided by the metasurface but also the operating costs brought by its reconfigurability, such as powering and cabling. These costs can present challenges, particularly in indoor dense spaces (IDSs). A self-sustainable metasurface (SSM), which retains reconfigurability unlike a static metasurface (SMS), achieves a lower operating cost than a reconfigurable intelligent surface (RIS) by being self-sustainable through power harvesting. In this paper, in order to find a better trade-off between metasurface gain, coverage, and operating cost, the design and performance of an SSM-assisted indoor mmWave communication system are investigated. We first simplify the design of the SSM-assisted system by considering the use of SSMs in a preset-based manner and the formation of coverage groups by associating SSMs with the closest user equipments (UEs). We propose a two-stage iterative algorithm to maximize the minimum data rate in the system by jointly deciding the association between the UEs and the SSMs, the phase-shifts of the SSMs, and allocating time resources for each UE. The non-convexities that exist in the proposed optimization problem are tackled using the feasible point pursuit successive convex approximation method and the concave-convex procedure. To understand the best scenario for using SSM, the resulting performance is compared with that achieved with RIS and SMS. Our numerical results indicate that SSMs are best utilized in a small environment where self-sustainability is easier to achieve when the budget for operating costs is tight.

翻译：在设计面向室内环境的超表面辅助系统时，不仅需要考虑超表面带来的性能增益与覆盖扩展，还必须考虑其可重构性所带来的运行成本，例如供电与布线。这些成本可能带来挑战，尤其在室内密集空间（IDSs）中。自维持超表面（SSM）不同于静态超表面（SMS），它保持了可重构性，同时通过能量收集实现自维持，从而比可重构智能表面（RIS）具有更低的运行成本。本文为在超表面增益、覆盖范围与运行成本之间寻求更优权衡，研究了SSM辅助的室内毫米波通信系统的设计与性能。我们首先通过考虑以预设方式使用SSM，并将SSM与最近用户设备（UEs）关联形成覆盖组，简化了SSM辅助系统的设计。我们提出了一种两阶段迭代算法，通过联合决策UEs与SSMs之间的关联关系、SSMs的相移配置以及为每个UE分配时间资源，以最大化系统中最小的数据速率。所提优化问题中存在的非凸性通过可行点追踪逐次凸逼近方法和凹凸过程进行处理。为理解使用SSM的最佳场景，将所得性能与采用RIS和SMS时达到的性能进行比较。我们的数值结果表明，在运行成本预算紧张且自维持更易实现的小型环境中，SSM能得到最佳利用。