Approximative Matrix Inverse Computations for Very-large MIMO and Applications to Linear Pre-coding Systems
Prabhu, Hemanth LU ; Rodrigues, Joachim LU ; Edfors, Ove LU
and Rusek, Fredrik
LU
(2013)
WCNC (wireless communications and networking conference)
p.2710-2715
- Abstract
- In very-large multiple-input multiple-output (MIMO) systems, the BS (base station) is equipped with very large number of antennas as compared to previously considered systems. There are various advantages of increasing the number of antennas, and some schemes would require handling large
matrices for joint processing (pre-coding) at the base station. The dirty paper coding (DPC) is an optimal pre-coding scheme and has a very high complexity. However with increasing number of BS antennas linear pre-coding performance tends
to that of the optimal DPC. Although linear pre-coding is less complex than DPC, there is a need to compute pseudo inverses of large matrices. In this paper we present a low complexity approximation of... (More) - In very-large multiple-input multiple-output (MIMO) systems, the BS (base station) is equipped with very large number of antennas as compared to previously considered systems. There are various advantages of increasing the number of antennas, and some schemes would require handling large
matrices for joint processing (pre-coding) at the base station. The dirty paper coding (DPC) is an optimal pre-coding scheme and has a very high complexity. However with increasing number of BS antennas linear pre-coding performance tends
to that of the optimal DPC. Although linear pre-coding is less complex than DPC, there is a need to compute pseudo inverses of large matrices. In this paper we present a low complexity approximation of down-link Zero Forcing linear pre-coding for very-large multi-user MIMO systems. Approximation using a Neumann series expansion is opted for inversion of matrices over traditional exact computations, by making use of special properties of the matrices, thereby reducing the cost of hardware. With this approximation of linear pre-coding,
we can significantly reduce the computational complexity for large enough systems, i.e., where we have enough BS antenna elements. For the investigated case of 8 users, we obtain 90% of the full ZF sum rate, with lower computational complexity, when the number of BS antennas per user is about 20 or more. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/3288141
- author
- Prabhu, Hemanth
LU
; Rodrigues, Joachim
LU
; Edfors, Ove
LU
and Rusek, Fredrik
LU
- organization
- publishing date
- 2013
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- linear precoding, massive mimo, matrix inverse approximation
- host publication
- [Host publication title missing]
- pages
- 5 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- WCNC (wireless communications and networking conference)
- conference location
- Shanghai, China
- conference dates
- 2013-04-02
- external identifiers
-
- wos:000326048102137
- scopus:84881564216
- project
- Distributed antenna systems for efficient wireless systems
- language
- English
- LU publication?
- yes
- id
- 8fe68d84-fc23-4970-89ae-0bae28eef268 (old id 3288141)
- date added to LUP
- 2016-04-04 10:15:40
- date last changed
- 2024-03-30 09:40:11
@inproceedings{8fe68d84-fc23-4970-89ae-0bae28eef268,
abstract = {{In very-large multiple-input multiple-output (MIMO) systems, the BS (base station) is equipped with very large number of antennas as compared to previously considered systems. There are various advantages of increasing the number of antennas, and some schemes would require handling large<br/><br>
matrices for joint processing (pre-coding) at the base station. The dirty paper coding (DPC) is an optimal pre-coding scheme and has a very high complexity. However with increasing number of BS antennas linear pre-coding performance tends<br/><br>
to that of the optimal DPC. Although linear pre-coding is less complex than DPC, there is a need to compute pseudo inverses of large matrices. In this paper we present a low complexity approximation of down-link Zero Forcing linear pre-coding for very-large multi-user MIMO systems. Approximation using a Neumann series expansion is opted for inversion of matrices over traditional exact computations, by making use of special properties of the matrices, thereby reducing the cost of hardware. With this approximation of linear pre-coding,<br/><br>
we can significantly reduce the computational complexity for large enough systems, i.e., where we have enough BS antenna elements. For the investigated case of 8 users, we obtain 90% of the full ZF sum rate, with lower computational complexity, when the number of BS antennas per user is about 20 or more.}},
author = {{Prabhu, Hemanth and Rodrigues, Joachim and Edfors, Ove and Rusek, Fredrik}},
booktitle = {{[Host publication title missing]}},
keywords = {{linear precoding; massive mimo; matrix inverse approximation}},
language = {{eng}},
pages = {{2710--2715}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
title = {{Approximative Matrix Inverse Computations for Very-large MIMO and Applications to Linear Pre-coding Systems}},
url = {{https://lup.lub.lu.se/search/files/5498921/5364198.pdf}},
year = {{2013}},
}