Search arXiv⌕ Search
Home/Archive/arXiv

arXiv · 2510.10647

A Parametric Power Model of Upper Mid-Band (FR3) Base Stations for 6G

Emanuele Peschiera·Sangbu Yun·Youngjoo Lee·Liesbet Van der Perre·François Rottenberg
View original source ↗Read source document ↗Export metadata ↓

Abstract

Increasing attention is given to the upper mid-band or Frequency Range 3 (FR3), from 7 to 24 GHz, in the research towards sixth-generation (6G) networks. Promises of offering large data rates at favorable propagation conditions are leading to novel FR3 base station (BS) architectures, with up to thousands of antenna elements and radio-frequency (RF) chains. This work investigates the power consumption of prospective FR3 BSs and its relation to the delivered data rates. We model the power consumed by digital and analog signal processing, power amplifiers (PAs), and supply and cooling during four phases (data, signaling, micro-sleep, and idle) in downlink and uplink. Hybrid partially-connected beamforming is compared to fully-digital one. Results show that, for BS arrays with $1024$ antennas at $30\%$ of load, the PA consumes most of the power when $64$ or less RF chains are utilized, while the digital and analog processing consumption takes over when the number of RF chains is $512$ or more. The digital plus analog processing consumes $2\times$ to $4\times$ more than the PA for fully-digital beamforming. Hybrid beamforming achieves $1.3$ Gbit/s/user in downlink while improving the energy efficiency by $1.4\times$ compared to fully-digital beamforming.

Explore related subjects

eess.SP

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Emanuele Peschiera, Sangbu Yun, Youngjoo Lee, Liesbet Van der Perre, François Rottenberg. 2025-10-12. A Parametric Power Model of Upper Mid-Band (FR3) Base Stations for 6G. https://doi.org/10.1109/icassp55912.2026.11464669

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

Multi-Carrier Rydberg Atomic Quantum Receivers with Enhanced Bandwidth Feature for Communication and Sensing

Rydberg atomic quantum receivers (RAQRs) have attracted significant attention in recent years due to their ultra-high sensitivity. Although capable of precisely detecting the amplitude and phase of weak signals, conventional RAQRs face inherent limitations in accurately receiving wideband RF signals, due to the discrete nature of atomic energy levels and their intrinsic instantaneous bandwidth constraints. These limitations hinder their direct application to multi-carrier communication and sensing. To address this issue, this paper proposes a multi-carrier Rydberg atomic quantum receiver (MC-RAQR) structure with five energy levels. We derive the amplitude and phase of the MC-RAQR and extract the baseband electrical signal for signal processing. In terms of multi-carrier communication and sensing, we analyze the channel capacity and accuracy of angle of arrival (AoA) and distance parameters, respectively. Numerical results validate our proposed model, showing that the MC-RAQR can achieve up to a bandwidth of 11.7 MHz, which is 17-fold larger than the conventional RAQRs. As a result, the channel capacity and the resolution for multi-target sensing are improved significantly. Specifically, the channel capacity of MC-RAQR is 110-fold and 2.8-fold larger than the classical RF receivers and RAQRs, respectively. For sensing performance, the RMSE of AoA estimation for MC-RAQR exhibits 7.6-fold reduction, compared with the conventional RAQRs. Furthermore, the RMSE of distance estimation is $634$-fold smaller than that of the root-CRB of classical RF receivers, showing the superior performance of the MC-RAQR. This demonstrates its compatibility with waveforms such as orthogonal frequency-division multiplexing (OFDM) and its significant advantages for multi-carrier signal reception.

eess.SP↗
arXiv2026

Channel Estimation in MIMO Systems Aided by Microwave Linear Analog Computers (MiLACs)

Microwave linear analog computers (MiLACs) have recently emerged as a promising solution for future gigantic multiple-input multiple-output (MIMO) systems, enabling beamforming with greatly reduced hardware and computational cost. However, channel estimation for MiLAC-aided systems remains an open problem. Conventional least squares (LS) and minimum mean square error (MMSE) estimation rely on intensive digital computation, which undermines the computational advantage offered by MiLACs. In this letter, we propose efficient LS and MMSE channel estimation schemes for MiLAC-aided MIMO systems. By designing the training precoder and combiner implemented by lossless and reciprocal MiLACs, the proposed schemes perform LS and MMSE estimation in the analog domain, leaving only simple digital scaling. They achieve identical estimation performance to their digital counterparts while significantly reducing computational complexity. Numerical results verify the effectiveness of the proposed schemes.

eess.SP↗
arXiv2026

Joint Subcarrier Phase Recovery for Nonlinearity Mitigation

We propose a low-complexity phase recovery scheme that simultaneously mitigates laser phase noise and fiber nonlinearity across several subcarriers. In a long single-span link with Raman amplification, the scheme achieves 0.9 dB gain with 99 real multiplications per complex symbol.

eess.SP↗