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CSI-Free Optimization of Reconfigurable Intelligent Surfaces with Interference by Using Multiport Network Theory

A. Abrardo

TL;DR

This work addresses RIS optimization for uplink communications in the presence of interference without relying on CSI estimation. It introduces a physically-grounded multiport network (MP) model that captures mutual coupling and structural scattering, contrasting it with traditional CT models. A CSI-free optimization framework based on channel correlation matrices is developed via an alternating optimization algorithm, including an Neumann-series–based linearization for tractable updates. Numerical results demonstrate that the proposed offline CSI-free design can closely approach the performance of CSI-enabled schemes in several scenarios, while highlighting the importance of realistic MP modeling for interference handling and RIS effectiveness in practice.

Abstract

Reconfigurable Intelligent Surfaces (RIS) will play a pivotal role in next-generation wireless systems. Despite efforts to minimize pilot overhead associated with channel estimation, the necessity of configuring the RIS multiple times before obtaining reliable Channel State Information (CSI) may significantly diminish their benefits. Therefore, we propose a CSI-free approach that explores the feasibility of optimizing the RIS for the uplink of a communication system in the presence of interfering users without relying on CSI estimation but leveraging solely some a priori statistical knowledge of the channel. In this context, we consider a multiport network model that accounts for several aspects overlooked by traditional RIS models used in Communication Theory, such as mutual coupling among scattering elements and the presence of structural scattering. The proposed approach targets the maximization of the average achievable rate and is shown to achieve performance that, in some cases, can be very close to the case where the RIS is optimized leveraging perfect CSI.

CSI-Free Optimization of Reconfigurable Intelligent Surfaces with Interference by Using Multiport Network Theory

TL;DR

This work addresses RIS optimization for uplink communications in the presence of interference without relying on CSI estimation. It introduces a physically-grounded multiport network (MP) model that captures mutual coupling and structural scattering, contrasting it with traditional CT models. A CSI-free optimization framework based on channel correlation matrices is developed via an alternating optimization algorithm, including an Neumann-series–based linearization for tractable updates. Numerical results demonstrate that the proposed offline CSI-free design can closely approach the performance of CSI-enabled schemes in several scenarios, while highlighting the importance of realistic MP modeling for interference handling and RIS effectiveness in practice.

Abstract

Reconfigurable Intelligent Surfaces (RIS) will play a pivotal role in next-generation wireless systems. Despite efforts to minimize pilot overhead associated with channel estimation, the necessity of configuring the RIS multiple times before obtaining reliable Channel State Information (CSI) may significantly diminish their benefits. Therefore, we propose a CSI-free approach that explores the feasibility of optimizing the RIS for the uplink of a communication system in the presence of interfering users without relying on CSI estimation but leveraging solely some a priori statistical knowledge of the channel. In this context, we consider a multiport network model that accounts for several aspects overlooked by traditional RIS models used in Communication Theory, such as mutual coupling among scattering elements and the presence of structural scattering. The proposed approach targets the maximization of the average achievable rate and is shown to achieve performance that, in some cases, can be very close to the case where the RIS is optimized leveraging perfect CSI.
Paper Structure (18 sections, 45 equations, 8 figures)

This paper contains 18 sections, 45 equations, 8 figures.

Table of Contents

  1. Introduction
  2. Contribution
  3. Paper Outline and Notation
  4. System Model
  5. RIS Models
  6. Communication Theory (CT) Model
  7. Multiport Network (MP) Model
  8. Comparison between CT and MP models
  9. RIS Optimization
  10. Problem Formulation
  11. Solution of \ref{['opt_2_1']}
  12. Solution for the MP case
  13. Solution for the CT model
  14. Numerical Results
  15. Model considered for RIS optimization
  16. ...and 3 more sections

Figures (8)

  • Figure 1: RIS-aided communication system.
  • Figure 2: Angle spread for correlation evaluation
  • Figure 3: Convergence behavior for the OPT-NoCSI algorithm for the case where $N_u = 3$ and for three values of dipoles' distances: $d_x = \lambda/2$, $d_x = \lambda/4$, and $d_x = \lambda/8$. The node positions are assumed such that the two interfering nodes are located at the same distance of 10 meters from the useful node, with angles between the nodes differing by $\pi/8$. The results for four different position uncertainty, namely $\sigma = 0$ m, $\sigma = 0.1$ m, $\sigma = 0.5$ m and $\sigma = 1$ m, are reported in Figs. (a), (b), (c) and (d), respectively.
  • Figure 4: Rate $R$ in \ref{['ERG_Rate']} evaluated through simulations considering $\sigma = 0.5$ m in the case of $N_u = 2$, with the intended UE positioned at $P_0 = 10\left(\cos \frac{\pi}{8}, \sin \frac{\pi}{8}, 0\right)$ while the interfering user is positioned at 12 possible different positions, $P_i = 10\left\{\cos [\pi/8 + (i-1)\pi/32], \sin[\pi/8 + (i-1)\pi/32],0\right\}$, with $i = 1,\ldots,12$. The case (a) refers to $d_x = \frac{\lambda}{2}$, while the case (b) reports the case $d_x = \frac{\lambda}{4}$
  • Figure 5: Rate $R$ in \ref{['ERG_Rate']} evaluated through simulations considering $\sigma = 1$ m for the same setting of Fig. \ref{['Fig1_rate']}.
  • ...and 3 more figures