Efficient downlink power allocation algorithms for cell-free massive mimo systems
Chakraborty, Sucharita ; Demir, Ozlem Tugfe ; Bjornson, Emil and Giselsson, Pontus LU
(2021)
In IEEE Open Journal of the Communications Society
2.
p.168-186
- Abstract
Cell-free Massive MIMO systems consist of a large number of geographically distributed access points (APs) that serve the users by coherent joint transmission. The spectral efficiency (SE) achieved by each user depends on the power allocation: which APs that transmit to which users and with what power. In this article, we revisit the max-min and sum-SE power allocation policies, which have previously been approached using high-complexity general-purpose solvers. We develop and compare several different high-performance low-complexity power allocation algorithms that are appropriate for use in large systems. We propose two new algorithms for sum-SE power optimization inspired by weighted minimum mean square error (WMMSE) minimization and... (More)
Cell-free Massive MIMO systems consist of a large number of geographically distributed access points (APs) that serve the users by coherent joint transmission. The spectral efficiency (SE) achieved by each user depends on the power allocation: which APs that transmit to which users and with what power. In this article, we revisit the max-min and sum-SE power allocation policies, which have previously been approached using high-complexity general-purpose solvers. We develop and compare several different high-performance low-complexity power allocation algorithms that are appropriate for use in large systems. We propose two new algorithms for sum-SE power optimization inspired by weighted minimum mean square error (WMMSE) minimization and fractional programming (FP). Further, one new FP-based algorithm is proposed for max-min fair power allocation. The alternating direction method of multipliers (ADMM) is used to solve specific convex subproblems in the proposed algorithms. Our ADMM reformulations lead to multiple small-sized subproblems with closed-form solutions. The proposed algorithms find global or local optimal power allocation solutions for large-scale systems but with reduced computational time compared to previous work.
(Less)
- author
- Chakraborty, Sucharita
; Demir, Ozlem Tugfe
; Bjornson, Emil
and Giselsson, Pontus
LU
- organization
- publishing date
- 2021
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- ADMM, Cell-free massive MIMO, fractional programming, max-min fairness, power allocation, sum-SE maximization, WMMSE
- in
- IEEE Open Journal of the Communications Society
- volume
- 2
- article number
- 9293031
- pages
- 19 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- external identifiers
-
- scopus:85122048517
- ISSN
- 2644-125X
- DOI
- 10.1109/OJCOMS.2020.3044280
- language
- English
- LU publication?
- yes
- additional info
- Publisher Copyright: © 2020 IEEE.
- id
- a88aa175-dd2f-4d5f-be0c-2ee77ecc91eb
- date added to LUP
- 2022-02-21 15:02:03
- date last changed
- 2023-11-21 03:02:46
@article{a88aa175-dd2f-4d5f-be0c-2ee77ecc91eb,
abstract = {{<p>Cell-free Massive MIMO systems consist of a large number of geographically distributed access points (APs) that serve the users by coherent joint transmission. The spectral efficiency (SE) achieved by each user depends on the power allocation: which APs that transmit to which users and with what power. In this article, we revisit the max-min and sum-SE power allocation policies, which have previously been approached using high-complexity general-purpose solvers. We develop and compare several different high-performance low-complexity power allocation algorithms that are appropriate for use in large systems. We propose two new algorithms for sum-SE power optimization inspired by weighted minimum mean square error (WMMSE) minimization and fractional programming (FP). Further, one new FP-based algorithm is proposed for max-min fair power allocation. The alternating direction method of multipliers (ADMM) is used to solve specific convex subproblems in the proposed algorithms. Our ADMM reformulations lead to multiple small-sized subproblems with closed-form solutions. The proposed algorithms find global or local optimal power allocation solutions for large-scale systems but with reduced computational time compared to previous work. </p>}},
author = {{Chakraborty, Sucharita and Demir, Ozlem Tugfe and Bjornson, Emil and Giselsson, Pontus}},
issn = {{2644-125X}},
keywords = {{ADMM; Cell-free massive MIMO; fractional programming; max-min fairness; power allocation; sum-SE maximization; WMMSE}},
language = {{eng}},
pages = {{168--186}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
series = {{IEEE Open Journal of the Communications Society}},
title = {{Efficient downlink power allocation algorithms for cell-free massive mimo systems}},
url = {{http://dx.doi.org/10.1109/OJCOMS.2020.3044280}},
doi = {{10.1109/OJCOMS.2020.3044280}},
volume = {{2}},
year = {{2021}},
}