# Robust Precoding for Resilient Cell-Free Networks

arXiv: https://arxiv.org/abs/2512.00531 · HTML: https://mlsanity.com/paper/2512.00531/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 5 of its 37 references that are in the map.
- First posted on arXiv 29 Nov 2025.

## Builds on (most cited first, 5 of 5)

- [Scalable Cell-Free Massive MIMO Systems](https://mlsanity.com/paper/1908.03119/) (2019)
- [Design of Robust Adaptive Beamforming Algorithms Based on Low-Rank and Cross-Correlation Techniques](https://mlsanity.com/paper/1606.01313/) (2016)
- [Ubiquitous Cell-Free Massive MIMO Communications](https://mlsanity.com/paper/1804.03421/) (2018)
- [User-centric Cell-free Massive MIMO Networks: A Survey of Opportunities, Challenges and Solutions](https://mlsanity.com/paper/2104.14589/) (2021)
- [Rate-Splitting assisted Massive Machine-Type Communications in Cell-Free Massive MIMO](https://mlsanity.com/paper/2201.07508/) (2022)

## Abstract (arXiv)

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.