On the Modelling of Coarse Vector Quantization in Distributed Massive MIMO

Alister Burr, Dick Maryopi

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


We consider coarse vector quantization for the fronthaul of distributed or cell-free massive MIMO, which is also related to Cloud Radio Access Network (C-RAN) architecture. We propose the use of lattice vector quantization (LVQ) based on Voronoi codes, and discuss how they can be adapted for efficient quantization of correlated signals, using a near-ellipsoidal Voronoi codebook. The Bussgang decomposition is extended to model these quantizers, and some numerical results obtained. A comparison of the quantization error with that of the Linde-Buzo-Gray (LBG) shows that for strongly correlated signals, while simple Voronoi LVQ has around 3 dB poorer performance, the near-ellipsoidal codebook is very close to LBG.

Original languageEnglish
Title of host publication2021 IEEE Statistical Signal Processing Workshop, SSP 2021
PublisherIEEE Computer Society
Number of pages5
ISBN (Electronic)9781728157672
Publication statusPublished - 19 Aug 2021
Event21st IEEE Statistical Signal Processing Workshop, SSP 2021 - Virtual, Rio de Janeiro, Brazil
Duration: 11 Jul 202114 Jul 2021

Publication series

NameIEEE Workshop on Statistical Signal Processing Proceedings


Conference21st IEEE Statistical Signal Processing Workshop, SSP 2021
CityVirtual, Rio de Janeiro

Bibliographical note

Funding Information:
The work described in this paper was supported in part by Indonesia Endowment Fund for Education (LPDP), and in part by the EU Horizon 2020 Programme, Project SPOTLIGHT (MCSA-ITN-2016-722788)

Publisher Copyright:
© 2021 IEEE.


  • Bussgang decomposition
  • C-RAN
  • distributed massive MIMO
  • Vector quantization

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