A Low Complexity Massive MIMO Detection Scheme Using Angular-Domain Processing
(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:
https://lup.lub.lu.se/record/b9c1c220-bb87-4fdf-9de0-14bb089e958a
- author
- Mahdavi, Mojtaba LU ; Edfors, Ove LU ; Öwall, Viktor LU and Liu, Liang LU
- organization
- publishing date
- 2018-11-26
- 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
- 2024-09-17 16:04:39
@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}}, booktitle = {{IEEE Global Conference on Signal and Information Processing (GlobalSIP)}}, isbn = {{978-1-7281-1295-4}}, keywords = {{massive MIMO; angular domain; channel compression; CSI matrix; MIMO detection; low complexity; channel sparsity}}, language = {{eng}}, month = {{11}}, 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}}, doi = {{10.1109/GlobalSIP.2018.8646483}}, year = {{2018}}, }