On the Total Energy Efficiency of Cell-Free Massive MIMO
We consider the cell-free massive multiple-input multiple-output (MIMO) downlink, where a very large number of distributed multiple-antenna access points (APs) serve many single-antenna users in the same time-frequency resource. A simple (distributed) conjugate beamforming scheme is applied at each...
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| Published in | IEEE transactions on green communications and networking Vol. 2; no. 1; pp. 25 - 39 |
|---|---|
| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Piscataway
IEEE
01.03.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subjects | |
| Online Access | Get full text |
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| Abstract | We consider the cell-free massive multiple-input multiple-output (MIMO) downlink, where a very large number of distributed multiple-antenna access points (APs) serve many single-antenna users in the same time-frequency resource. A simple (distributed) conjugate beamforming scheme is applied at each AP via the use of local channel state information (CSI). This CSI is acquired through time-division duplex operation and the reception of uplink training signals transmitted by the users. We derive a closed-form expression for the spectral efficiency taking into account the effects of channel estimation errors and power control. This closed-form result enables us to analyze the effects of backhaul power consumption, the number of APs, and the number of antennas per AP on the total energy efficiency, as well as, to design an optimal power allocation algorithm. The optimal power allocation algorithm aims at maximizing the total energy efficiency, subject to a per-user spectral efficiency constraint and a per-AP power constraint. Compared with the equal power control, our proposed power allocation scheme can double the total energy efficiency. Furthermore, we propose AP selections schemes, in which each user chooses a subset of APs, to reduce the power consumption caused by the backhaul links. With our proposed AP selection schemes, the total energy efficiency increases significantly, especially for large numbers of APs. Moreover, under a requirement of good quality-of-service for all users, cell-free massive MIMO outperforms the colocated counterpart in terms of energy efficiency. |
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| AbstractList | We consider the cell-free massive multiple-input multiple-output (MIMO) downlink, where a very large number of distributed multiple-antenna access points (APs) serve many single-antenna users in the same time-frequency resource. A simple (distributed) conjugate beamforming scheme is applied at each AP via the use of local channel state information (CSI). This CSI is acquired through time-division duplex operation and the reception of uplink training signals transmitted by the users. We derive a closed-form expression for the spectral efficiency taking into account the effects of channel estimation errors and power control. This closed-form result enables us to analyze the effects of backhaul power consumption, the number of APs, and the number of antennas per AP on the total energy efficiency, as well as, to design an optimal power allocation algorithm. The optimal power allocation algorithm aims at maximizing the total energy efficiency, subject to a per-user spectral efficiency constraint and a per-AP power constraint. Compared with the equal power control, our proposed power allocation scheme can double the total energy efficiency. Furthermore, we propose AP selections schemes, in which each user chooses a subset of APs, to reduce the power consumption caused by the backhaul links. With our proposed AP selection schemes, the total energy efficiency increases significantly, especially for large numbers of APs. Moreover, under a requirement of good quality-of-service for all users, cell-free massive MIMO outperforms the colocated counterpart in terms of energy efficiency. |
| Author | Tran, Le-Nam Duong, Trung Q. Ngo, Hien Quoc Larsson, Erik G. Matthaiou, Michail |
| Author_xml | – sequence: 1 givenname: Hien Quoc orcidid: 0000-0002-3367-2220 surname: Ngo fullname: Ngo, Hien Quoc email: hien.ngo@qub.ac.uk organization: Institute of Electronics, Communications and Information Technology, Queen's University Belfast, Belfast, U.K – sequence: 2 givenname: Le-Nam orcidid: 0000-0002-9317-9980 surname: Tran fullname: Tran, Le-Nam email: nam.tran@ucd.ie organization: School of Electrical and Electronic Engineering, University College Dublin, Dublin 4, Ireland – sequence: 3 givenname: Trung Q. orcidid: 0000-0002-4703-4836 surname: Duong fullname: Duong, Trung Q. email: trung.q.duong@qub.ac.uk organization: Institute of Electronics, Communications and Information Technology, Queen's University Belfast, Belfast, U.K – sequence: 4 givenname: Michail orcidid: 0000-0001-9235-7741 surname: Matthaiou fullname: Matthaiou, Michail email: m.matthaiou@qub.ac.uk organization: Institute of Electronics, Communications and Information Technology, Queen's University Belfast, Belfast, U.K – sequence: 5 givenname: Erik G. orcidid: 0000-0002-7599-4367 surname: Larsson fullname: Larsson, Erik G. email: erik.g.larsson@liu.se organization: Department of Electrical Engineering, Linköping University, Linköping, Sweden |
| BackLink | https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-149660$$DView record from Swedish Publication Index |
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| Snippet | We consider the cell-free massive multiple-input multiple-output (MIMO) downlink, where a very large number of distributed multiple-antenna access points (APs)... |
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| SubjectTerms | Algorithms antenna arrays Antennas AP selection schemes array signal processing backhaul power consumption Beamforming Cell-free massive MIMO cell-free massive multiple input multiple output downlink Channel estimation channel estimation errors Closed form solutions closed-form expression Communication channels conjugate beamforming conjugate beamforming scheme distributed multiple-antenna access points Downlink Duplex operation energy conservation Energy efficiency Exact solutions massive MIMO Mathematical analysis MIMO MIMO (control systems) MIMO communication network MIMO optimal power allocation algorithm Optimization per-AP power constraint per-user spectral efficiency constraint power allocation scheme Power consumption Power control Power demand Power efficiency Power management quality of service single-antenna users spectral efficiency telecommunication power management time-division duplex operation total energy efficiency Uplink wireless channels |
| Title | On the Total Energy Efficiency of Cell-Free Massive MIMO |
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