# Optimizing Fronthaul Quantization for Flexible User Load in Cell-Free Massive MIMO

arXiv: https://arxiv.org/abs/2510.06734 · HTML: https://mlsanity.com/paper/2510.06734/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 4 of its 17 references that are in the map.
- First posted on arXiv 8 Oct 2025.

## Builds on (most cited first, 4 of 4)

- [Scalable Cell-Free Massive MIMO Systems](https://mlsanity.com/paper/1908.03119/) (2019)
- [Ultra-Dense Cell-Free Massive MIMO for 6G: Technical Overview and Open Questions](https://mlsanity.com/paper/2401.03898/) (2024)
- [Subspace-Based Pilot Decontamination in User-Centric Scalable Cell-Free Wireless Networks](https://mlsanity.com/paper/2203.00714/) (2022)
- [Fairness Scheduling in User-Centric Cell-Free Massive MIMO Wireless Networks](https://mlsanity.com/paper/2307.00850/) (2023)

## Abstract (arXiv)

We investigate the physical layer (PHY) spectral efficiency and fronthaul network load of a scalable user-centric cell-free massive MIMO system. Each user-centric cluster processor responsible for cluster-level signal processing is located at one of multiple decentralized units (DUs). Thus, the radio units in the cluster must exchange data with the corresponding DU over the fronthaul. Because the fronthaul links have limited capacity, this data must be quantized before it is sent over the fronthaul. We consider a routed fronthaul network, where the cluster processor placement and fronthaul traffic routing are jointly optimized with a mixed-integer linear program. For different numbers of users in the network, we investigate the effect of fronthaul quantization rates, a system parameter computed based on rate-distortion theory. Our results show that with optimized quantization rates, the fronthaul load is quite stable for a wide range of user loads without significant PHY performance loss. This demonstrates that the cell-free massive MIMO PHY and fronthaul network are resilient to varying user densities.