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Robust Precoding for Resilient Cell-Free Networks

Saeed Mashdour, André R. Flores, Rodrigo C. de Lamare

TL;DR

The paper addresses the challenge of robust downlink precoding in cell-free massive MIMO under imperfect CSI. It proposes a robust precoder that minimizes a weighted sum of the desired-signal MSE and residual interference leakage, explicitly incorporating CSI error statistics and a total power constraint. A closed-form precoder is derived via a Lagrangian, and an alternating optimization algorithm with a single matrix inversion per iteration is used, starting from an MMSE initialization. Simulations show significant sum-rate gains over ZF and MMSE precoders across SNR values, with a favorable robustness-complexity trade-off for resilient CF-mMIMO networks.

Abstract

This paper presents a robust precoder design for resilient cell-free massive MIMO (CF-mMIMO) systems that minimizes the weighted sum of desired signal mean square error (MSE) and residual interference leakage power under a total transmit power constraint. The proposed robust precoder incorporates channel state information (CSI) error statistics to enhance resilience against CSI imperfections. We employ an alternating optimization algorithm initialized with a minimum MSE-type solution, which iteratively refines the precoder while maintaining low computational complexity and ensuring fast convergence. Numerical results show that the proposed method significantly outperforms conventional linear precoders, providing an effective balance between performance and computational efficiency.

Robust Precoding for Resilient Cell-Free Networks

TL;DR

The paper addresses the challenge of robust downlink precoding in cell-free massive MIMO under imperfect CSI. It proposes a robust precoder that minimizes a weighted sum of the desired-signal MSE and residual interference leakage, explicitly incorporating CSI error statistics and a total power constraint. A closed-form precoder is derived via a Lagrangian, and an alternating optimization algorithm with a single matrix inversion per iteration is used, starting from an MMSE initialization. Simulations show significant sum-rate gains over ZF and MMSE precoders across SNR values, with a favorable robustness-complexity trade-off for resilient CF-mMIMO networks.

Abstract

This paper presents a robust precoder design for resilient cell-free massive MIMO (CF-mMIMO) systems that minimizes the weighted sum of desired signal mean square error (MSE) and residual interference leakage power under a total transmit power constraint. The proposed robust precoder incorporates channel state information (CSI) error statistics to enhance resilience against CSI imperfections. We employ an alternating optimization algorithm initialized with a minimum MSE-type solution, which iteratively refines the precoder while maintaining low computational complexity and ensuring fast convergence. Numerical results show that the proposed method significantly outperforms conventional linear precoders, providing an effective balance between performance and computational efficiency.

Paper Structure

This paper contains 9 sections, 42 equations, 2 figures, 1 algorithm.

Table of Contents

  1. Introduction
  2. Network and Channel Models and Problem Formulation
  3. Network Architecture
  4. Channel Representation
  5. Problem Statement
  6. Proposed Robust Precoding Method
  7. Computational Complexity Analysis
  8. Numerical Results
  9. Conclusions

Figures (2)

  • Figure 1: Sum-rate comparison of the proposed robust precoder, ZF, and MMSE with equal power loading and $\alpha=0.15$, $L = 16$, $N = 4$, $K = 128$, $n = 16$, and C-ESG scheduling.
  • Figure 2: Computational complexity comparison of the proposed robust precoder, ZF, and MMSE in terms of floating point operations, when $n = 16$ UEs are scheduled.