Few-Bit CSI Acquisition for Centralized Cell-Free Massive MIMO with Spatial Correlation

Dick Maryopi, Alister Burr

Research output: Chapter in Book/Report/Conference proceedingConference contribution


The availability and accuracy of Channel State Information (CSI) play a crucial role for coherent detection in almost every communication system. Particularly in the recently proposed cell-free massive MIMO system, in which a large number of distributed Access Points (APs) is connected to a Central processing Unit (CPU) for joint decoding, acquiring CSI at the CPU may improve performance through the use of detection algorithms such as minimum mean square error (MMSE) or zero forcing (ZF). There are also significant challenges, especially the increase in fronthaul load arising from the transfer of high precision CSI, with the resulting complexity and scalability issues. In this paper, we address these CSI acquisition problems by utilizing vector quantization with precision of only a few bits and we show that the accuracy of the channel estimate at the CPU can be increased by exploiting the spatial correlation subject to this limited fronthaul load. Further, we derive an estimator for the simple Quantize-and-Estimate (QE) strategy based on the Bussgang theorem and compare its performance to Estimate-and-Quantize (EQ) in terms of Mean Squared Error (MSE). Our simulation results indicate that the QE with few-bit vector quantization can outperform EQ and individual scalar quantization at moderate SNR for small numbers of bits per dimension.

Original languageEnglish
Title of host publication2019 IEEE Wireless Communications and Networking Conference, WCNC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538676462
Publication statusPublished - Apr 2019
Event2019 IEEE Wireless Communications and Networking Conference, WCNC 2019 - Marrakesh, Morocco
Duration: 15 Apr 201919 Apr 2019

Publication series

NameIEEE Wireless Communications and Networking Conference, WCNC
ISSN (Print)1525-3511


Conference2019 IEEE Wireless Communications and Networking Conference, WCNC 2019

Bibliographical note

Funding Information:
The paper was supported by Indonesia Endowment Fund for Education (LPDP) and in part by the European Horizon 2020 Programme under GA H2020-MSCA-ITN-2016-722788.

Publisher Copyright:
© 2019 IEEE.


  • Bussgang
  • Cell-Free
  • Channel Estimation
  • Fronthaul
  • Massive MIMO
  • Vector Quantization

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