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Iteratively Weighted MMSE Uplink Precoding for Cell-Free Massive MIMO
  • Zhe Wang, Beijing Jiaotong University
  • Jiayi Zhang, Beijing Jiaotong University
  • Hien Quoc Ngo, Queen's University Belfast
  • Bo Ai, Beijing Jiaotong University
  • Méroúane Debbah, Mohamed bin Zayed University of Artificial Intelligence & Technology Innovation Institute, Masdar City, Abu Dhabi
Document Type

In this paper, we investigate a cell-free massive MIMO system with both access points and user equipments equipped with multiple antennas over the Weichselberger Rayleigh fading channel. We study the uplink spectral efficiency (SE) based on a two-layer decoding structure with maximum ratio (MR) or local minimum mean-square error (MMSE) combining applied in the first layer and optimal large-scale fading decoding method implemented in the second layer, respectively. To maximize the weighted sum SE, an uplink precoding structure based on an Iteratively Weighted sum-MMSE (I-WMMSE) algorithm using only channel statistics is proposed. Furthermore, with MR combining applied in the first layer, we derive novel achievable SE expressions and optimal precoding structures in closed-form. Numerical results validate our proposed results and show that the I-WMMSE precoding can achieve excellent sum SE performance. Copyright © 2022, The Authors. All rights reserved.

Publication Date
  • Fading channels; Iterative decoding; Mean square error; Rayleigh fading; Structural optimization

Preprint: arXiv

Citation Information
Z. Wang, J. Zhang, H. Q. Ngo, B, Ai, and M. Debbah, "Iteratively weighted MMSE uplink precoding for cell-free massive MIMO," 2022, arXiv:2201.11299