An Optimization Driven Link SINR Assurance in RIS-assisted Indoor Networks

TL;DR

This paper proposes an optimization approach using Integer Linear Programming to deploy Reconfigurable Intelligent Surfaces in indoor mmWave networks, enhancing connectivity and reducing outages by improving SINR.

Contribution

It introduces a novel ILP-based method for RIS deployment in indoor networks, optimizing link quality and connectivity considering interference nulling and QoS constraints.

Findings

Optimal RIS deployment improves SINR and connectivity.

Significant reduction in link outages with the proposed method.

Heuristics approximate optimal solutions effectively.

Abstract

Future smart factories are expected to deploy applications over high-performance indoor wireless channels in the millimeter-wave (mmWave) bands, which on the other hand are susceptible to high path losses and Line-of Sight (LoS) blockages. Low-cost Reconfigurable Intelligent Surfaces (RISs) can provide great opportunities in such scenarios, due to its ability to alleviate LoS link blockages. In this paper, we formulate a combinatorial optimization problem, solved with Integer Linear Programming (ILP) to optimally maintain connectivity by solving the problem of allocating RIS to robots in a wireless indoor network. Our model exploits the characteristic of nulling interference from RISs by tuning RIS reflection coefficients. We further consider Quality-of-Service (QoS) at receivers in terms of Signal-to-Interference-plus-Noise Ratio (SINR) and connection outages due to insufficient transmission quality service. Numerical results for optimal solutions and heuristics show the benefits of optimally deploying RISs by providing continuous connectivity through SINR, which significantly reduces outages due to link quality.