In this work, we consider the deployment of reconfigurable intelligent surfaces (RISs) to extend the coverage of a millimeter-wave (mmWave) network in indoor dense spaces. We first integrate RIS into ray-tracing simulations to realistically capture the propagation characteristics, then formulate a non-convex optimization problem that minimizes the number of RISs under rate constraints. We propose a feasible point pursuit and successive convex approximation-based algorithm, which solves the problem by jointly selecting the RIS locations, optimizing the RIS phase-shifts, and allocating time resources to user equipments (UEs). The numerical results demonstrate substantial coverage extension by using at least four RISs, and a data rate of 130 Mbit/s is guaranteed for UEs in the considered area of an airplane cabin.
@article{arxiv.2302.09257,
title = {mmWave Coverage Extension Using Reconfigurable Intelligent Surfaces in Indoor Dense Spaces},
author = {Zhenyu Li and Ozan Alp Topal and Özlem Tuğfe Demir and Emil Björnson and Cicek Cavdar},
journal= {arXiv preprint arXiv:2302.09257},
year = {2023}
}
Comments
6 pages 8 figures. Accepted to be presented in IEEE ICC 2023