IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v10y2022i11p1900-d830043.html
   My bibliography  Save this article

Scalable Cell-Free Massive MIMO with Multiple CPUs

Author

Listed:
  • Feiyang Li

    (School of Information Science and Technology, Nantong University, Nantong 226019, China)

  • Qiang Sun

    (School of Information Science and Technology, Nantong University, Nantong 226019, China)

  • Xiaodi Ji

    (School of Information Science and Technology, Nantong University, Nantong 226019, China)

  • Xiaomin Chen

    (School of Information Science and Technology, Nantong University, Nantong 226019, China)

Abstract

In this paper, we consider the uplink of a scalable cell-free massive MIMO (CF-M-MIMO) system where user equipments (UEs) are served only by a subset of access points (APs). All APs are physically divided into predetermined “real clusters”, which are linked to different cooperative central processing units (CPUs). Based on the cooperative nature of the considered communications framework, we assume that each UE is affiliated with a “virtual cluster”, which is associated with some APs coming from different real clusters. Thanks to the degrees of cooperation among multiple CPUs, the uplink spectral efficiencies (SEs) of four different levels are analyzed. To achieve system scalability, the CF-M-MIMO system with multiple CPUs is introduced, which leads to lower SE. To this end, we design a joint combining method based on statistical channel state informations (CSIs), which not only has low complexity but also improves the SE of the system. Simulation results indicate that the average rate of our proposed method can be improved by about 30%.

Suggested Citation

  • Feiyang Li & Qiang Sun & Xiaodi Ji & Xiaomin Chen, 2022. "Scalable Cell-Free Massive MIMO with Multiple CPUs," Mathematics, MDPI, vol. 10(11), pages 1-17, June.
  • Handle: RePEc:gam:jmathe:v:10:y:2022:i:11:p:1900-:d:830043
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/10/11/1900/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/10/11/1900/
    Download Restriction: no
    ---><---

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:10:y:2022:i:11:p:1900-:d:830043. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.