4.7 Article

Local Partial Zero-Forcing Combining for Cell-Free Massive MIMO Systems

Journal

IEEE TRANSACTIONS ON COMMUNICATIONS
Volume 69, Issue 12, Pages 8459-8473

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCOMM.2021.3110214

Keywords

Uplink; Massive MIMO; Antennas; Interference; Computer architecture; Microprocessors; Power control; Cell-free massive MIMO; power control; performance analysis; zero-forcing

Funding

  1. National Key R&D Program of China [2020YFB1807201]
  2. National Natural Science Foundation of China [61971027, U1834210, 61961130391]
  3. Beijing Natural Science Foundation [L202013]
  4. Frontiers Science Center for Smart High-speed Railway System
  5. Royal Society Newton Advanced Fellowship [NA191006]
  6. Fundamental Research Funds for the Central Universities, China [2020JBZD005]
  7. Project of China Shenhua [GJNY-20-01-1]
  8. Swedish Research Council [2019-05068]
  9. Swedish Research Council [2019-05068] Funding Source: Swedish Research Council

Ask authors/readers for more resources

This paper examines the impact of different signal processing schemes on efficiency in cell-free massive MIMO systems, finding that local regularized ZF provides the highest spectral efficiency. Protective weak PFZF is preferable when the number of pilot sequences or antennas per access point is large or small. Additionally, through fractional power control, performance for weak users can be improved, achieving uniformly good service for all users in a scalable manner.
Cell-free massive multiple-input multiple-output (MIMO) provides more uniform spectral efficiency (SE) for users (UEs) than cellular technology. The main challenge to achieve the benefits of cell-free massive MIMO is to realize signal processing in a scalable way. In this paper, we consider scalable full-pilot zero-forcing (FZF), partial FZF (PFZF), protective weak PFZF (PWPFZF), and local regularized ZF (LRZF) combining by exploiting channel statistics. We derive closed-form expressions of the uplink SE for FZF, PFZF, and PWPFZF combining with large-scale fading decoding over independent Rayleigh fading channels, taking channel estimation errors and pilot contamination into account. Moreover, we investigate the impact of the number of pilot sequences, antennas per AP, and APs on the performance. Numerical results show that LRZF provides the highest SE. However, PWPFZF is preferable when the number of pilot sequences is large and the number of antennas per AP is small. The reason is that PWPFZF has lower computational complexity and the SE expression can be computed in closed-form. Furthermore, we investigate the performance of PWPFZF combining with fractional power control and the numerical results show that it improves the performance of weak UEs and realizes uniformly good service for all UEs in a scalable fashion.

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