Fronthaul-Efficient Cell-Free Massive MIMO via Stream-Adaptive Resolution Control
Abstract
We consider the uplink of a fronthaul-constrained cell-free massive MIMO system with a single multi-antenna user equipment (UE) transmitting multiple spatial streams to distributed access points (APs). Due to heterogeneous channel conditions and limited fronthaul capacity, uniform-resolution quantization across APs and streams is highly inefficient. To address this, we propose a stream- and AP-adaptive resolution control framework that jointly optimizes the transmit power and per-AP per-stream quantization resolutions. By leveraging a distributed implementation of singular-value decomposition (SVD)-based processing, the data streams are decoupled at the APs, enabling flexible fronthaul compression across both spatial streams and APs. The resulting non-convex optimization problem is tackled using a weighted minimum mean-squared error (WMMSE)-based block coordinate descent algorithm with semi-closed-form updates.
Related
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BibTeX
@misc{demir2026fronthaulefficient,
title = {{Fronthaul-Efficient Cell-Free Massive MIMO via Stream-Adaptive Resolution Control}},
author = {Özlem Tuğfe Demir and Sinan Gezici},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.26150},
eprint = {2609.26150},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.26150},
}
RIS
TY - UNPB
TI - Fronthaul-Efficient Cell-Free Massive MIMO via Stream-Adaptive Resolution Control
AU - Özlem Tuğfe Demir
AU - Sinan Gezici
PY - 2026
DA - 2026/09/01
PB - arXiv
DO - 10.48550/arxiv.2609.26150
UR - https://arxiv.org/abs/2609.26150
AB - We consider the uplink of a fronthaul-constrained cell-free massive MIMO system with a single multi-antenna user equipment (UE) transmitting multiple spatial streams to distributed access points (APs). Due to heterogeneous channel conditions and limited fronthaul capacity, uniform-resolution quantization across APs and streams is highly inefficient. To address this, we propose a stream- and AP-adaptive resolution control framework that jointly optimizes the transmit power and per-AP per-stream quantization resolutions. By leveraging a distributed implementation of singular-value decomposition (SVD)-based processing, the data streams are decoupled at the APs, enabling flexible fronthaul compression across both spatial streams and APs. The resulting non-convex optimization problem is tackled using a weighted minimum mean-squared error (WMMSE)-based block coordinate descent algorithm with semi-closed-form updates.
ER -