Max-Min Rate of Cell-Free Massive MIMO Uplink with Optimal Uniform Quantization

Manijeh Bashar*, Kanapathippillai Cumanan, Alister G. Burr, Hien Quoc Ngo, Merouane Debbah, Pei Xiao

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

81 Citations (Scopus)
285 Downloads (Pure)


Cell-free massive multiple-input-multiple-output (MIMO) is considered, where distributed access points (APs) multiply the received signal by the conjugate of the estimated channel, and send back a quantized version of this weighted signal to a central processing unit (CPU). For the first time, we present a performance comparison between the case of perfect fronthaul links, the case when the quantized version of the estimated channel and the quantized signal are available at the CPU, and the case when only the quantized weighted signal is available at the CPU. The Bussgang decomposition is used to model the effect of quantization. The max-min problem is studied, where the minimum rate is maximized with the power and fronthaul capacity constraints. To deal with the non-convex problem, the original problem is decomposed into two sub-problems (referred to as receiver filter design and power allocation). Geometric programming (GP) is exploited to solve the power allocation problem whereas a generalized eigenvalue problem is solved to design the receiver filter. An iterative scheme is developed and the optimality of the proposed algorithm is proved through uplink-downlink duality. A user assignment algorithm is proposed which significantly improves the performance. The numerical results demonstrate the superiority of the proposed schemes.

Original languageEnglish
Article number8756286
Pages (from-to)6796-6815
Number of pages20
JournalIEEE Transactions on Communications
Issue number10
Early online date08 Jul 2019
Publication statusPublished - Oct 2019


  • Cell-free Massive MIMO
  • generalized eigenvalue
  • geometric programming
  • limited fronthaul

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


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