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STAR-RIS-Aided Cell-Free Massive MIMO with Imperfect Hardware

Zeping Sui, Hien Quoc Ngo, Michail Matthaiou

TL;DR

The paper studies STAR-RIS-aided CF-mMIMO under imperfect hardware and spatially correlated fading, addressing hardware impairments, phase noise, and RIS phase errors. It develops linear MMSE channel estimation that accounts for pilot contamination and derives a closed-form downlink ergodic SE under MR precoding, using only channel statistics. Key contributions include the MMSE cascaded-channel estimator, a tractable MR-based SE bound, and insightful analysis of hardware quality factors and RIS phase-error effects. Numerical results show significant SE gains of STAR-RIS CF-mMIMO over conventional CF-mMIMO even with hardware imperfections, and demonstrate the impact of RIS-phase and oscillator quality on performance. The work supports the practical viability of STAR-RIS in large-scale CF-mMIMO by quantifying performance under realistic non-idealities.

Abstract

This paper considers a simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS)-aided cell-free massive multiple-input multiple-output (CF-mMIMO) system, accounting for imperfect hardware in spatially correlated fading channels. Specifically, we consider the hardware impairments and phase noise at transceivers, as well as the phase shift errors generated within the STAR-RIS. We commence by introducing the STAR-RIS signal model, channel model, and imperfect hardware components. Then, the linear minimum mean-square error (MMSE) channel estimate is derived with pilot contamination, which provides sufficient information for sequential data processing. Moreover, a channel capacity lower bound is derived in the case of a finite number of RIS elements and access points (APs), while a closed-form expression for the downlink ergodic spectral efficiency (SE) for maximum ratio (MR) precoding is also deduced, where only the channel statistics are used. Our numerical results demonstrate that the STAR-RIS-aided CF-mMIMO system achieves higher SE compared to the conventional CF-mMIMO system, even with imperfect hardware.

STAR-RIS-Aided Cell-Free Massive MIMO with Imperfect Hardware

TL;DR

The paper studies STAR-RIS-aided CF-mMIMO under imperfect hardware and spatially correlated fading, addressing hardware impairments, phase noise, and RIS phase errors. It develops linear MMSE channel estimation that accounts for pilot contamination and derives a closed-form downlink ergodic SE under MR precoding, using only channel statistics. Key contributions include the MMSE cascaded-channel estimator, a tractable MR-based SE bound, and insightful analysis of hardware quality factors and RIS phase-error effects. Numerical results show significant SE gains of STAR-RIS CF-mMIMO over conventional CF-mMIMO even with hardware imperfections, and demonstrate the impact of RIS-phase and oscillator quality on performance. The work supports the practical viability of STAR-RIS in large-scale CF-mMIMO by quantifying performance under realistic non-idealities.

Abstract

This paper considers a simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS)-aided cell-free massive multiple-input multiple-output (CF-mMIMO) system, accounting for imperfect hardware in spatially correlated fading channels. Specifically, we consider the hardware impairments and phase noise at transceivers, as well as the phase shift errors generated within the STAR-RIS. We commence by introducing the STAR-RIS signal model, channel model, and imperfect hardware components. Then, the linear minimum mean-square error (MMSE) channel estimate is derived with pilot contamination, which provides sufficient information for sequential data processing. Moreover, a channel capacity lower bound is derived in the case of a finite number of RIS elements and access points (APs), while a closed-form expression for the downlink ergodic spectral efficiency (SE) for maximum ratio (MR) precoding is also deduced, where only the channel statistics are used. Our numerical results demonstrate that the STAR-RIS-aided CF-mMIMO system achieves higher SE compared to the conventional CF-mMIMO system, even with imperfect hardware.
Paper Structure (10 sections, 18 equations, 3 figures)

This paper contains 10 sections, 18 equations, 3 figures.

Table of Contents

  1. Introduction
  2. System Model
  3. STAR-RIS Signal Model and Operation Protocol
  4. Phase Shift Errors
  5. Channel Model
  6. Phase Noise Model
  7. Channel Estimation
  8. Downlink Data Transmission
  9. Numerical Results
  10. Conclusions

Figures (3)

  • Figure 1: Illustration of the considered STAR-RIS-aided CF-mMIMO system.
  • Figure 2: CDF of the sum downlink SE for STAR-RIS-aided CF-mMIMO with different $\gamma_T$ and $\gamma_R$ and CF-mMIMO with ideal hardware ($M=20,K_R=K_T=3,N=128,L=4$).
  • Figure 3: Downlink sum SE versus the number of AP $M$ operating for different RIS phase error parameter $\vartheta_p$ ($K_R=K_T=3,N=64,L=4,\gamma_T=\gamma_R=1$).