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Maximizing Spectral and Energy Efficiency in Multi-user MIMO OFDM Systems with RIS and Hardware Impairment

Mohammad Soleymani, Ignacio Santamaria, Aydin Sezgin, Eduard Jorswieck

TL;DR

This paper investigates the performance of various RIS technologies like regular, simultaneously transmit and reflect, and multi-sector beyond diagonal (BD) RIS in multi-user multiple-input multiple-output (MIMO) OFDM broadcast channels (BC) and reveals that RIS can significantly improve the system performance even when the number of RIS elements is relatively low.

Abstract

An emerging technology to enhance the spectral efficiency (SE) and energy efficiency (EE) of wireless communication systems is reconfigurable intelligent surface (RIS), which is shown to be very powerful in single-carrier systems. However, in multi-user orthogonal frequency division multiplexing (OFDM) systems, RIS may not be as promising as in single-carrier systems since an independent optimization of RIS elements at each sub-carrier is impossible in multi-carrier systems. Thus, this paper investigates the performance of various RIS technologies like regular (reflective and passive), simultaneously transmit and reflect (STAR), and multi-sector beyond diagonal (BD) RIS in multi-user multiple-input multiple-output (MIMO) OFDM broadcast channels (BC). This requires to formulate and solve a joint MIMO precoding and RIS optimization problem. The obtained solution reveals that RIS can significantly improve the system performance even when the number of RIS elements is relatively low. Moreover, we develop resource allocation schemes for STAR-RIS and multi-sector BD-RIS in MIMO OFDM BCs, and show that these RIS technologies can outperform a regular RIS, especially when the regular RIS cannot assist the communications for all the users.

Maximizing Spectral and Energy Efficiency in Multi-user MIMO OFDM Systems with RIS and Hardware Impairment

TL;DR

This paper investigates the performance of various RIS technologies like regular, simultaneously transmit and reflect, and multi-sector beyond diagonal (BD) RIS in multi-user multiple-input multiple-output (MIMO) OFDM broadcast channels (BC) and reveals that RIS can significantly improve the system performance even when the number of RIS elements is relatively low.

Abstract

An emerging technology to enhance the spectral efficiency (SE) and energy efficiency (EE) of wireless communication systems is reconfigurable intelligent surface (RIS), which is shown to be very powerful in single-carrier systems. However, in multi-user orthogonal frequency division multiplexing (OFDM) systems, RIS may not be as promising as in single-carrier systems since an independent optimization of RIS elements at each sub-carrier is impossible in multi-carrier systems. Thus, this paper investigates the performance of various RIS technologies like regular (reflective and passive), simultaneously transmit and reflect (STAR), and multi-sector beyond diagonal (BD) RIS in multi-user multiple-input multiple-output (MIMO) OFDM broadcast channels (BC). This requires to formulate and solve a joint MIMO precoding and RIS optimization problem. The obtained solution reveals that RIS can significantly improve the system performance even when the number of RIS elements is relatively low. Moreover, we develop resource allocation schemes for STAR-RIS and multi-sector BD-RIS in MIMO OFDM BCs, and show that these RIS technologies can outperform a regular RIS, especially when the regular RIS cannot assist the communications for all the users.
Paper Structure (26 sections, 3 theorems, 35 equations, 12 figures, 1 table)

This paper contains 26 sections, 3 theorems, 35 equations, 12 figures, 1 table.

Table of Contents

  1. Introduction
  2. Literature review
  3. Motivation
  4. Contribution
  5. System model
  6. RIS model
  7. Concept of multi-sector BD-RIS
  8. Effective channels in frequency domain
  9. Operational modes for multi-sector BD-RIS
  10. I/Q imbalance model
  11. Signal model
  12. Problem statement
  13. Optimization algorithms to solve \ref{['ar-opt']}
  14. Updating transmit covariance matrices
  15. Updating RIS elements
  16. ...and 11 more sections

Key Result

Lemma 1

Equation 8 can be rewritten in a real domain as where $\underline{\mathbf{y}}_i$, $\underline{\mathbf{x}}_i$, and $\underline{\mathbf{n}}_i$ are, respectively, the real decomposition of ${\bf y}_i$, ${\bf x}_i$, and $\mathbf{\Gamma}_{r1,i}{\bf n}_{i}\!+\!\mathbf{\Gamma}_{r2,i}{\bf n}^*_{i}$. Note that the effective noise at the output of the rece

Figures (12)

  • Figure 1: A broadcast channel aided by a multi-sector BD-RIS.
  • Figure 2: Average minimum rate versus $P$ for the case without RIS (No-RIS), randomly configured RIS (RIS-Rand), and optimized regular RIS (RIS) with $N_{\mathsf{B}}=N_{\mathsf{U}}=2$, $K=3$, $N_{\mathsf{R}}=100$, $L=2$, $N=2$, and $N_i=16$.
  • Figure 3: Improvements by RIS versus $P$ for $N_{\mathsf{B}}=2$, $N_{\mathsf{U}}=2$, $K=3$, $L=1$, $N=1$, and different $N_i$.
  • Figure 4: Improvements by RIS versus $P$ for $N_{\mathsf{B}}=2$, $N_{\mathsf{U}}=2$, $K=3$, $L=2$, $N=2$, and $N_i=16$.
  • Figure 5: Impact of IQI on the average minimum rate of users for $N_{\mathsf{B}}=2$, $N_{\mathsf{U}}=2$, $K=2$, $N_{\mathsf{R}}=100$, $L=2$, $N=2$, and $N_i=16$.
  • ...and 7 more figures

Theorems & Definitions (3)

  • Lemma 1: soleymani2020improper
  • Lemma 2
  • Lemma 3