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A Comparison of the Uplink Performance of Cell-Free Massive MIMO using Three Linear Combining Schemes: Full-Pilot Zero Forcing with Access Point Selection, Matched-Filter and Local-Minimum-Mean-Square Error
Author(s)
Date Issued
2020-06-12
Date Available
2021-02-01T17:42:01Z
Abstract
In this paper, three types of linear receiver for the uplink of cell-free massive multiple-input-multiple-output (MIMO) will be studied to gain a clear comparison and understanding of their performance. In a cell-free massive MIMO system, a large number of randomly distributed access points (APs) cooperate to serve a much smaller number of users in the same time-frequency resource. The three receivers of interest are matched-filter (MF) combining, full-pilot zero forcing (fpZF) combining and the local-minimum-mean-squared error (L-MMSE) combining. The APs use locally obtained channel state information to perform the combining. Max-min fairness power control is utilised for the MF and fpZF combining to ensure uniformly good service for all users in the system. We note that max-min fairness power control is not required for the L-MMSE combining since the L-MMSE scheme itself can provide the worst served users with the same spectral efficiency as the MF with max-min fairness. In this paper an AP selection scheme is proposed for the fpZF combining. In particular, the proposed AP selection scheme provides users with reasonably good spectral efficiency using a subset of APs rather than all APs serving all users, which proves to increase the overall energy efficiency of the system. The results show that the fpZF consistently outperforms the MF and L-MMSE even while using only a subset of the APs.
Sponsorship
Science Foundation Ireland
University College Dublin
Type of Material
Conference Publication
Publisher
IEEE
Copyright (Published Version)
2020 IEEE
Web versions
Language
English
Status of Item
Peer reviewed
Journal
2020 31st Irish Signals and Systems Conference (ISSC)
Conference Details
The 31st Irish Signals and Systems Conference (ISSC 2020), Online Conference, 11-12 June 2020
This item is made available under a Creative Commons License
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conference_101719.pdf
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