# Optimal Bilinear Equalizer for Cell-Free Massive MIMO Systems over Correlated Rician Channels

arXiv: https://arxiv.org/abs/2407.18531 · HTML: https://mlsanity.com/paper/2407.18531/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 26 Jul 2024.

## Built on by (most cited first, 2 of 2)

- [Unified Error Correction Code Transformer with Low Complexity](https://mlsanity.com/paper/2410.03364/) (2024)
- [Statistical Channel Fingerprint Construction for Massive MIMO: A Unified Tensor Learning Framework](https://mlsanity.com/paper/2604.27574/) (2026)

## Abstract (arXiv)

In this paper, we explore the low-complexity optimal bilinear equalizer (OBE) combining scheme design for cell-free massive multiple-input multiple-output networks with spatially correlated Rician fading channels. We provide a spectral efficiency (SE) performance analysis framework for both the centralized and distributed processing schemes with bilinear equalizer (BE)-structure combining schemes applied. The BE-structured combining is a set of schemes that are constructed by the multiplications of channel statistics-based BE matrices and instantaneous channel estimates. Notably, we derive closed-form achievable SE expressions for centralized and distributed BE-structured combining schemes. We propose one centralized and two distributed OBE schemes: Centralized OBE (C-OBE), Distributed OBE based on Global channel statistics (DG-OBE), and Distributed OBE based on Local channel statistics (DL-OBE), which maximize their respective SE expressions. OBE matrices in these schemes are tailored based on varying levels of channel statistics. Notably, we obtain new and insightful closed-form results for the C-OBE, DG-OBE, and DL-OBE combining schemes. Numerical results demonstrate that the proposed OBE schemes can achieve excellent SE, even in scenarios with severe pilot contamination.