Resolution-Adaptive All-Digital Spatial Equalization for mmWave Massive MU-MIMO
Paper in proceeding, 2021

All-digital basestation (BS) architectures for millimeter-wave (mmWave) massive multi-user multiple-input multiple-output (MU-MIMO), which equip each radio-frequency chain with dedicated data converters, have advantages in spectral efficiency, flexibility, and baseband-processing simplicity over hybrid analog-digital solutions. For all-digital architectures to be competitive with hybrid solutions in terms of power consumption, novel signal-processing methods and baseband architectures are necessary. In this paper, we demonstrate that adapting the resolution of the analog-to-digital converters (ADCs) and spatial equalizer of an all-digital system to the communication scenario (e.g., the number of users, modulation scheme, and propagation conditions) enables orders-of-magnitude power savings for realistic mmWave channels. For example, for a 256-BS-antenna 16-user system supporting 1 GHz bandwidth, a traditional baseline architecture designed for a 64-user worst-case scenario would consume 23 W in 28 nm CMOS for the ADC array and the spatial equalizer, whereas a resolution-adaptive architecture is able to reduce the power consumption by 6.7×.

Author

Oscar Castañeda

Swiss Federal Institute of Technology in Zürich (ETH)

Seyed Hadi Mirfarshbafan

Swiss Federal Institute of Technology in Zürich (ETH)

Shahaboddin Ghajari

Cornell University

Alyosha Molnar

Cornell University

Sven Jacobsson

Ericsson

Giuseppe Durisi

Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks, Communication Systems

Christoph Studer

Swiss Federal Institute of Technology in Zürich (ETH)

IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC

386-390
978-1-6654-2851-4 (ISBN)

2021 IEEE 22nd International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)
Lucca, Italy,

Areas of Advance

Information and Communication Technology

Subject Categories

Telecommunications

Communication Systems

Signal Processing

DOI

10.1109/SPAWC51858.2021.9593110

More information

Latest update

1/25/2022