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Impact of Quantization in Decentralized Processing for Large Multi-Antenna Architectures

Alegría, Juan Vidal LU orcid ; Rusek, Fredrik LU and Lozano, Angel (2022) 56th Asilomar Conference on Signals, Systems and Computers, ACSSC 2022 p.1351-1356
Abstract

The demand for an increased number of antennas at base stations is driving research on decentralized processing schemes aimed at reducing the information volume that has to be transferred to, and processed at, a central processing unit (CPU). Some of these schemes can reduce the dimensions of the data while achieving information-lossless processing with respect to centralized architectures. However, little is known about the impact of quantization in these decentralized schemes. Moreover, it is unclear if an information-lossless reduction of dimensions directly corresponds to a reduction in the bit-rate that has to be transmitted to the CPU after quantization. This paper studies how quantization affects the performance of decentralized... (More)

The demand for an increased number of antennas at base stations is driving research on decentralized processing schemes aimed at reducing the information volume that has to be transferred to, and processed at, a central processing unit (CPU). Some of these schemes can reduce the dimensions of the data while achieving information-lossless processing with respect to centralized architectures. However, little is known about the impact of quantization in these decentralized schemes. Moreover, it is unclear if an information-lossless reduction of dimensions directly corresponds to a reduction in the bit-rate that has to be transmitted to the CPU after quantization. This paper studies how quantization affects the performance of decentralized processing. Bit rates after quantization of a received vector (in a centralized scheme) are contrasted with bit rates after quantization of post-processed vectors using various information-lossless dimension reductions that can potentially be applied in decentralized schemes.

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Please use this url to cite or link to this publication:
author
; and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
host publication
2022 56th Asilomar Conference on Signals, Systems, and Computers
editor
Matthews, Michael B.
pages
6 pages
publisher
IEEE Computer Society
conference name
56th Asilomar Conference on Signals, Systems and Computers, ACSSC 2022
conference location
Virtual, Online, United States
conference dates
2022-10-31 - 2022-11-02
external identifiers
  • scopus:85150179982
ISBN
9781665459068
DOI
10.1109/IEEECONF56349.2022.10051998
language
English
LU publication?
yes
id
8e921842-6658-46f4-b586-c33a0839883c
date added to LUP
2023-04-03 13:35:14
date last changed
2023-11-21 06:12:36
@inproceedings{8e921842-6658-46f4-b586-c33a0839883c,
  abstract     = {{<p>The demand for an increased number of antennas at base stations is driving research on decentralized processing schemes aimed at reducing the information volume that has to be transferred to, and processed at, a central processing unit (CPU). Some of these schemes can reduce the dimensions of the data while achieving information-lossless processing with respect to centralized architectures. However, little is known about the impact of quantization in these decentralized schemes. Moreover, it is unclear if an information-lossless reduction of dimensions directly corresponds to a reduction in the bit-rate that has to be transmitted to the CPU after quantization. This paper studies how quantization affects the performance of decentralized processing. Bit rates after quantization of a received vector (in a centralized scheme) are contrasted with bit rates after quantization of post-processed vectors using various information-lossless dimension reductions that can potentially be applied in decentralized schemes.</p>}},
  author       = {{Alegría, Juan Vidal and Rusek, Fredrik and Lozano, Angel}},
  booktitle    = {{2022 56th Asilomar Conference on Signals, Systems, and Computers}},
  editor       = {{Matthews, Michael B.}},
  isbn         = {{9781665459068}},
  language     = {{eng}},
  pages        = {{1351--1356}},
  publisher    = {{IEEE Computer Society}},
  title        = {{Impact of Quantization in Decentralized Processing for Large Multi-Antenna Architectures}},
  url          = {{http://dx.doi.org/10.1109/IEEECONF56349.2022.10051998}},
  doi          = {{10.1109/IEEECONF56349.2022.10051998}},
  year         = {{2022}},
}