Fronthaul Compression for Uplink Cloud-RAN with Finite-Alphabet Inputs: A Reverse Mercury/Waterfilling Approach
Abstract
The cloud radio access network (C-RAN) mitigates inter-cell interference by jointly processing the observations of distributed remote units (RUs) at a centralized unit (CU), but limited fronthaul capacity forces each RU to compress its received signal. Under transform-compress-forward, an RU transforms its signal and quantizes the resulting coefficients, with bit allocation distributing a finite bit budget across them. Classical reverse waterfilling assumes Gaussian sources, yet practical finite-alphabet symbols carry mutual information that saturates at log2 M, leaving bit allocation for such inputs unresolved. We address this by formulating bit allocation as maximizing the finite-alphabet generalized mutual information (GMI) achieved after linear MMSE (LMMSE) detection at the CU. Via the I-MMSE relation, this yields a fixed-point update whose converged solution decomposes into a vessel height, a shared water level, and a finite-alphabet mercury level; we term it {reverse mercury/waterfilling} (RMWF). Numerical results show that RMWF sustains end-to-end rate under tight fronthaul budgets and remains robust under antenna scaling, which is increasingly consequential as antenna counts outpace fronthaul capacity in modern C-RAN.
Related
- The reverse Ritz inclusion: computable bounds on the pseudospectra of an operator by those of a finite-rank compression
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- Uplink Hardware Impairments in OFDM-Based Cell-Free Massive MIMO With Impaired Wireless Fronthaul
BibTeX
@misc{shin2026fronthaul,
title = {{Fronthaul Compression for Uplink Cloud-RAN with Finite-Alphabet Inputs: A Reverse Mercury/Waterfilling Approach}},
author = {Subin Shin and Jaehoon Lee and Seok-Hwan Park and Jeonghun Park},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.21265},
eprint = {2609.21265},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.21265},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Fronthaul Compression for Uplink Cloud-RAN with Finite-Alphabet Inputs: A Reverse Mercury/Waterfilling Approach
AU - Subin Shin
AU - Jaehoon Lee
AU - Seok-Hwan Park
AU - Jeonghun Park
PY - 2026
DA - 2026/09/18
PB - arXiv
DO - 10.48550/arxiv.2609.21265
UR - https://arxiv.org/abs/2609.21265
AB - The cloud radio access network (C-RAN) mitigates inter-cell interference by jointly processing the observations of distributed remote units (RUs) at a centralized unit (CU), but limited fronthaul capacity forces each RU to compress its received signal. Under transform-compress-forward, an RU transforms its signal and quantizes the resulting coefficients, with bit allocation distributing a finite bit budget across them. Classical reverse waterfilling assumes Gaussian sources, yet practical finite-alphabet symbols carry mutual information that saturates at log_2 M, leaving bit allocation for such inputs unresolved. We address this by formulating bit allocation as maximizing the finite-alphabet generalized mutual information (GMI) achieved after linear MMSE (LMMSE) detection at the CU. Via the I-MMSE relation, this yields a fixed-point update whose converged solution decomposes into a vessel height, a shared water level, and a finite-alphabet mercury level; we term it {reverse mercury/waterfilling} (RMWF). Numerical results show that RMWF sustains end-to-end rate under tight fronthaul budgets and remains robust under antenna scaling, which is increasingly consequential as antenna counts outpace fronthaul capacity in modern C-RAN.
ER -