Uplink Power Control in Massive MIMO with Double Scattering Channels

Trinh Van Chien, Hien Quoc Ngo, Symeon Chatzinotas, Bjorn Ottersten, Merouane Debbah

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)
52 Downloads (Pure)


Massive multiple-input multiple-output (MIMO) is a key technology for improving the spectral and energy efficiency in 5G-and-beyond wireless networks. For a tractable analysis, most of the previous works on Massive MIMO have been focused on the system performance with complex Gaussian channel impulse responses under rich-scattering environments. In contrast, this paper investigates the uplink ergodic spectral efficiency (SE) of each user under the double scattering channel model. We derive a closed-form expression of the uplink ergodic SE by exploiting the maximum ratio (MR) combining technique based on imperfect channel state information. We further study the asymptotic SE behaviors as a function of the number of antennas at each base station (BS) and the number of scatterers available at each radio channel. We then formulate and solve a total energy optimization problem for the uplink data transmission that aims at simultaneously satisfying the required SEs from all the users with limited data power resource. Notably, our proposed algorithms can cope with the congestion issue appearing when at least one user is served by lower SE than requested. Numerical results illustrate the effectiveness of the closed-form ergodic SE over Monte-Carlo simulations. Besides, the system can still provide the required SEs to many users even under congestion.

Original languageEnglish
Pages (from-to)1989 - 2005
JournalIEEE Transactions on Wireless Communications
Issue number3
Early online date08 Sept 2021
Publication statusEarly online date - 08 Sept 2021

Bibliographical note

Publisher Copyright:


  • Antennas
  • Channel models
  • congestion issue
  • double scattering channels
  • Massive MIMO
  • Optimization
  • Rayleigh channels
  • Scattering
  • total transmit power minimization
  • Uplink

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Applied Mathematics


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