Fully Decentralized Approximate Zero-Forcing Precoding for Massive MIMO Systems
(2019) In IEEE Wireless Communications Letters 8(3). p.773-776- Abstract
We analyze the downlink of a massive multiuser multiple input, multiple output (MIMO) system where antenna units at the base station are connected in a daisy chain without a central processing unit and only possess local channel knowledge. For this setup, we develop and analyze a linear precoding algorithm for suppressing interuser interference. It is demonstrated that the algorithm is close to zero-forcing precoding in terms of performance for a large number of antennas. Moreover, we show that with careful scheduling of processing across antennas, requirements for interconnection throughput are reduced compared with the fully centralized solution. Favorable tradeoff between performance and interconnection throughput makes the daisy... (More)
We analyze the downlink of a massive multiuser multiple input, multiple output (MIMO) system where antenna units at the base station are connected in a daisy chain without a central processing unit and only possess local channel knowledge. For this setup, we develop and analyze a linear precoding algorithm for suppressing interuser interference. It is demonstrated that the algorithm is close to zero-forcing precoding in terms of performance for a large number of antennas. Moreover, we show that with careful scheduling of processing across antennas, requirements for interconnection throughput are reduced compared with the fully centralized solution. Favorable tradeoff between performance and interconnection throughput makes the daisy chain a viable candidate topology for real-life implementations of base stations in MIMO systems where the number of antennas is very large.
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- author
- Sarajlić, Muris LU ; Rusek, Fredrik LU ; Rodríguez Sánchez, Jesús LU ; Liu, Liang LU and Edfors, Ove LU
- organization
- publishing date
- 2019-06
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- daisy chain, decentralized processing, interference suppression, Massive MIMO
- in
- IEEE Wireless Communications Letters
- volume
- 8
- issue
- 3
- article number
- 8607077
- pages
- 4 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- external identifiers
-
- scopus:85067928827
- ISSN
- 2162-2337
- DOI
- 10.1109/LWC.2019.2892044
- language
- English
- LU publication?
- yes
- id
- 7b005068-2e1a-4b80-8c35-8de59b12da72
- date added to LUP
- 2019-07-09 16:10:22
- date last changed
- 2024-01-16 06:40:35
@article{7b005068-2e1a-4b80-8c35-8de59b12da72, abstract = {{<p>We analyze the downlink of a massive multiuser multiple input, multiple output (MIMO) system where antenna units at the base station are connected in a daisy chain without a central processing unit and only possess local channel knowledge. For this setup, we develop and analyze a linear precoding algorithm for suppressing interuser interference. It is demonstrated that the algorithm is close to zero-forcing precoding in terms of performance for a large number of antennas. Moreover, we show that with careful scheduling of processing across antennas, requirements for interconnection throughput are reduced compared with the fully centralized solution. Favorable tradeoff between performance and interconnection throughput makes the daisy chain a viable candidate topology for real-life implementations of base stations in MIMO systems where the number of antennas is very large.</p>}}, author = {{Sarajlić, Muris and Rusek, Fredrik and Rodríguez Sánchez, Jesús and Liu, Liang and Edfors, Ove}}, issn = {{2162-2337}}, keywords = {{daisy chain; decentralized processing; interference suppression; Massive MIMO}}, language = {{eng}}, number = {{3}}, pages = {{773--776}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, series = {{IEEE Wireless Communications Letters}}, title = {{Fully Decentralized Approximate Zero-Forcing Precoding for Massive MIMO Systems}}, url = {{http://dx.doi.org/10.1109/LWC.2019.2892044}}, doi = {{10.1109/LWC.2019.2892044}}, volume = {{8}}, year = {{2019}}, }