Hardware Efficient Approximative Matrix Inversion for Linear Pre-Coding in Massive MIMO
(2014) IEEE International Symposium on Circuits and Systems (ISCAS), 2014 p.1700-1703- Abstract
- This paper describes a hardware efficient linear pre-coder for Massive MIMO Base Stations (BSs) comprising a very large number of antennas, say, in the order of 100s, serving multiple users simultaneously. To avoid hardware demanding direct matrix inversions required for the Zero-Forcing (ZF) pre-coder, we use low complexity Neumann series based approximations. Furthermore, we propose a method to speed-up the convergence of the Neumann series by using tri-diagonal pre-condition matrices, which lowers the complexity even further. As a proof of concept a flexible VLSI architecture is presented with an implementation supporting matrix inversion of sizes up-to 16 × 16. In 65 nm CMOS, a throughput of 0.5M matrix inversions per sec is achieved... (More)
- This paper describes a hardware efficient linear pre-coder for Massive MIMO Base Stations (BSs) comprising a very large number of antennas, say, in the order of 100s, serving multiple users simultaneously. To avoid hardware demanding direct matrix inversions required for the Zero-Forcing (ZF) pre-coder, we use low complexity Neumann series based approximations. Furthermore, we propose a method to speed-up the convergence of the Neumann series by using tri-diagonal pre-condition matrices, which lowers the complexity even further. As a proof of concept a flexible VLSI architecture is presented with an implementation supporting matrix inversion of sizes up-to 16 × 16. In 65 nm CMOS, a throughput of 0.5M matrix inversions per sec is achieved at clock frequency of 420 MHz with a 104K gate count. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/4248962
- author
- Prabhu, Hemanth LU ; Edfors, Ove LU ; Rodrigues, Joachim LU ; Liu, Liang LU and Rusek, Fredrik LU
- organization
- publishing date
- 2014
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Massive MIMO, Pre-coder
- host publication
- [Host publication title missing]
- pages
- 4 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- IEEE International Symposium on Circuits and Systems (ISCAS), 2014
- conference location
- Melbourne, Australia
- conference dates
- 2014-06-01 - 2014-06-05
- external identifiers
-
- wos:000346488600427
- scopus:84907389998
- ISSN
- 0271-4310
- 2158-1525
- project
- Distributed antenna systems for efficient wireless systems
- language
- English
- LU publication?
- yes
- id
- e7dc60f9-6b5a-49ed-bd10-228c88baa113 (old id 4248962)
- date added to LUP
- 2016-04-01 10:42:22
- date last changed
- 2024-11-18 16:01:10
@inproceedings{e7dc60f9-6b5a-49ed-bd10-228c88baa113, abstract = {{This paper describes a hardware efficient linear pre-coder for Massive MIMO Base Stations (BSs) comprising a very large number of antennas, say, in the order of 100s, serving multiple users simultaneously. To avoid hardware demanding direct matrix inversions required for the Zero-Forcing (ZF) pre-coder, we use low complexity Neumann series based approximations. Furthermore, we propose a method to speed-up the convergence of the Neumann series by using tri-diagonal pre-condition matrices, which lowers the complexity even further. As a proof of concept a flexible VLSI architecture is presented with an implementation supporting matrix inversion of sizes up-to 16 × 16. In 65 nm CMOS, a throughput of 0.5M matrix inversions per sec is achieved at clock frequency of 420 MHz with a 104K gate count.}}, author = {{Prabhu, Hemanth and Edfors, Ove and Rodrigues, Joachim and Liu, Liang and Rusek, Fredrik}}, booktitle = {{[Host publication title missing]}}, issn = {{0271-4310}}, keywords = {{Massive MIMO; Pre-coder}}, language = {{eng}}, pages = {{1700--1703}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, title = {{Hardware Efficient Approximative Matrix Inversion for Linear Pre-Coding in Massive MIMO}}, url = {{https://lup.lub.lu.se/search/files/2068506/5364185.pdf}}, year = {{2014}}, }