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A Low Complexity Massive MIMO Detection Scheme Using Angular-Domain Processing

Mahdavi, Mojtaba LU ; Edfors, Ove LU ; Öwall, Viktor LU and Liu, Liang LU (2018) 2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP) p.181-185
Abstract
Signal processing complexity and required memory become problematic in massive MIMO systems as the dimension of channel state information (CSI) matrix grows significantly with the large number of antennas and users. To address these challenges, we propose the first angular-domain massive MIMO detection scheme, which is based on three concepts: transferring the baseband processing from the spatial domain to the angular domain; exploiting the sparsity of received beams to reduce the dimension of CSI matrix; and performing the whole detection and precoding in the angular domain using the reduced CSI matrix. We have measured the massive MIMO channel at 2.6 GHz with a 128-antenna linear array communicating with 16 users to evaluate our scheme.... (More)
Signal processing complexity and required memory become problematic in massive MIMO systems as the dimension of channel state information (CSI) matrix grows significantly with the large number of antennas and users. To address these challenges, we propose the first angular-domain massive MIMO detection scheme, which is based on three concepts: transferring the baseband processing from the spatial domain to the angular domain; exploiting the sparsity of received beams to reduce the dimension of CSI matrix; and performing the whole detection and precoding in the angular domain using the reduced CSI matrix. We have measured the massive MIMO channel at 2.6 GHz with a 128-antenna linear array communicating with 16 users to evaluate our scheme. Complexity analysis and simulations show that proposed idea leads to 40% – 70% reduction in the processing complexity and memory without significant performance loss, which significantly outperforms the antenna-domain schemes. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
massive MIMO, angular domain, channel compression, CSI matrix, MIMO detection, low complexity, channel sparsity
host publication
IEEE Global Conference on Signal and Information Processing (GlobalSIP)
pages
5 pages
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
conference name
2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP)
conference location
Anaheim, United States
conference dates
2018-11-26 - 2018-11-29
external identifiers
  • scopus:85063075221
ISBN
978-1-7281-1295-4
978-1-7281-1296-1
DOI
10.1109/GlobalSIP.2018.8646483
language
English
LU publication?
yes
id
b9c1c220-bb87-4fdf-9de0-14bb089e958a
date added to LUP
2019-03-21 01:51:26
date last changed
2019-07-07 05:07:20
@inproceedings{b9c1c220-bb87-4fdf-9de0-14bb089e958a,
  abstract     = {Signal processing complexity and required memory become problematic in massive MIMO systems as the dimension of channel state information (CSI) matrix grows significantly with the large number of antennas and users. To address these challenges, we propose the first angular-domain massive MIMO detection scheme, which is based on three concepts: transferring the baseband processing from the spatial domain to the angular domain; exploiting the sparsity of received beams to reduce the dimension of CSI matrix; and performing the whole detection and precoding in the angular domain using the reduced CSI matrix. We have measured the massive MIMO channel at 2.6 GHz with a 128-antenna linear array communicating with 16 users to evaluate our scheme. Complexity analysis and simulations show that proposed idea leads to 40% – 70% reduction in the processing complexity and memory without significant performance loss, which significantly outperforms the antenna-domain schemes.},
  author       = {Mahdavi, Mojtaba and Edfors, Ove and Öwall, Viktor and Liu, Liang},
  isbn         = {978-1-7281-1295-4},
  keyword      = {massive MIMO,angular domain,channel compression,CSI matrix,MIMO detection,low complexity,channel sparsity},
  language     = {eng},
  location     = {Anaheim, United States},
  month        = {12},
  pages        = {181--185},
  publisher    = {IEEE - Institute of Electrical and Electronics Engineers Inc.},
  title        = {A Low Complexity Massive MIMO Detection Scheme Using Angular-Domain Processing},
  url          = {http://dx.doi.org/10.1109/GlobalSIP.2018.8646483},
  year         = {2018},
}