Self-Sustainable Metasurface-Assisted mmWave Indoor Communication System

TL;DR

The paper addresses the challenge of indoor dense-space mmWave coverage with costly metasurface reconfigurability by proposing self-sustainable metasurfaces (SSMs) that harvest energy to power phase-control. It develops a two-stage, preset-based optimization framework to maximize the minimum data rate by jointly optimizing SSM phase-shifts, SSM-UE associations, and intra-network time allocation, using FPP-SCA and CCP to handle non-convexities. Through ray-tracing simulations in an aircraft cabin, the work compares SSMs to RIS and SMS, showing SSMs offer a favorable trade-off—significantly better than SMS and approaching RIS in small, budget-constrained settings, but with coverage limitations in larger environments due to sustainability constraints. The findings highlight SSMs as a viable, cost-aware alternative for IDS deployments, offering practical gains where operating costs are a critical consideration. Overall, the paper provides a scalable optimization methodology and a feasibility roadmap for deploying self-sustainable, reconfigurable metasurfaces in indoor mmWave networks.

Abstract

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.

Figures (16)

• Figure 1: Metasurface-assisted indoor communication system model.
• Figure 2: Illustration of the SSM with element splitting scheme.
• Figure 3: Illustration of the preset design.
• Figure 4: Flowchart of the two-stage iterative data rate optimization algorithm.
• Figure 5: Illustration of the metasurface, BS, and UE placement in the IDS. (a) The front view of the cabin; (b) the detailed metasurface structure, (c) the device layout in the cabin.