Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

Lens-Type Redirective Intelligent Surfaces for Multi-User MIMO Communication

Bamelak Tadele, Faouzi Bellili, Amine Mezghani, Md Jawwad Chowdhury, Haseeb Ur Rehman

TL;DR

The proposed RedRIS-based schemes are gauged against conventional reflective RIS-aided systems under both perfect and imperfect channel state information (CSI).

Abstract

This paper explores the idea of using redirective reconfigurable intelligent surfaces (RedRIS) to overcome many of the challenges associated with the conventional reflective RIS. We develop a framework for jointly optimizing the switching matrix of the lens-type RedRIS ports along with the active precoding matrix at the base station (BS) and the receive scaling factor. A joint non-convex optimization problem is formulated under the minimum mean-square error (MMSE) criterion with the aim to maximize the spectral efficiency of each user. In the single-cell scenario, the optimum active precoding matrix at the multi-antenna BS and the receive scaling factor are found in closed-form by applying Lagrange optimization, while the optimal switching matrix of the lens-type RedRIS is obtained by means of a newly developed alternating optimization algorithm. We then extend the framework to the multi-cell scenario with single-antenna base stations that are aided by the same lens-type RedRIS. We further present two methods for reducing the number of effective connections of the RedRIS ports that result in appreciable overhead savings while enhancing the robustness of the system. The proposed RedRIS-based schemes are gauged against conventional reflective RIS-aided systems under both perfect and imperfect channel state information (CSI). The simulation results show the superiority of the proposed schemes in terms of overall throughput while incurring much less control overhead.

Lens-Type Redirective Intelligent Surfaces for Multi-User MIMO Communication

TL;DR

The proposed RedRIS-based schemes are gauged against conventional reflective RIS-aided systems under both perfect and imperfect channel state information (CSI).

Abstract

This paper explores the idea of using redirective reconfigurable intelligent surfaces (RedRIS) to overcome many of the challenges associated with the conventional reflective RIS. We develop a framework for jointly optimizing the switching matrix of the lens-type RedRIS ports along with the active precoding matrix at the base station (BS) and the receive scaling factor. A joint non-convex optimization problem is formulated under the minimum mean-square error (MMSE) criterion with the aim to maximize the spectral efficiency of each user. In the single-cell scenario, the optimum active precoding matrix at the multi-antenna BS and the receive scaling factor are found in closed-form by applying Lagrange optimization, while the optimal switching matrix of the lens-type RedRIS is obtained by means of a newly developed alternating optimization algorithm. We then extend the framework to the multi-cell scenario with single-antenna base stations that are aided by the same lens-type RedRIS. We further present two methods for reducing the number of effective connections of the RedRIS ports that result in appreciable overhead savings while enhancing the robustness of the system. The proposed RedRIS-based schemes are gauged against conventional reflective RIS-aided systems under both perfect and imperfect channel state information (CSI). The simulation results show the superiority of the proposed schemes in terms of overall throughput while incurring much less control overhead.
Paper Structure (23 sections, 34 equations, 8 figures, 1 table, 4 algorithms)

This paper contains 23 sections, 34 equations, 8 figures, 1 table, 4 algorithms.

Table of Contents

  1. Introduction
  2. Background
  3. Contributions
  4. Paper organization and notations
  5. System model, assumptions, and problem formulation
  6. Constrained Optimization of Symmetric Permutation Matrix
  7. R-LS Module
  8. Projection Module
  9. Optimization of RedRIS-Aided Beamforming
  10. Finding the optimal switching matrix of the RedRIS ports
  11. Finding the optimal BS precoding matrix and receive scaling factor
  12. Reducing the number of Port Switchings
  13. Universal reduction
  14. Two-port solution for the single-user case
  15. Joint Optimization for the Multi-Cell Scenario
  16. ...and 8 more sections

Figures (8)

  • Figure 1: RedRIS-assisted multi-user MIMO system.
  • Figure 2: Block diagram of the proposed algorithm for symmetric permutation matrix optimization.
  • Figure 3: Block diagram of the proposed algorithm.
  • Figure 4: RedRIS-assisted communication for a multi-cell system.
  • Figure 5: (a) sum-rate versus transmit power (multi-user case), (b) sum-rate versus transmit power (single-user case), (c) sum-rate versus the number of RIS ports or reflection elements (multi-user case), and (d) sum-rate versus number of users. LOS component is present in the BS-RIS channels only.
  • ...and 3 more figures