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

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Main Authors: Göttsch, Fabian, Franke, Max, Pourdamghani, Arash, Caire, Giuseppe, Schmid, Stefan
Format: Preprint
Published: 2025
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author Göttsch, Fabian
Franke, Max
Pourdamghani, Arash
Caire, Giuseppe
Schmid, Stefan
author_facet Göttsch, Fabian
Franke, Max
Pourdamghani, Arash
Caire, Giuseppe
Schmid, Stefan
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2510_06734
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Optimizing Fronthaul Quantization for Flexible User Load in Cell-Free Massive MIMO
Göttsch, Fabian
Franke, Max
Pourdamghani, Arash
Caire, Giuseppe
Schmid, Stefan
Information Theory
Signal Processing
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.
title Optimizing Fronthaul Quantization for Flexible User Load in Cell-Free Massive MIMO
topic Information Theory
Signal Processing
url https://arxiv.org/abs/2510.06734