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Hardware distortion modeling for panel selection in large intelligent surfaces

Sheikhi, Ashkan LU orcid ; Alegría, Juan Vidal LU orcid and Edfors, Ove LU orcid (2024) 58th Asilomar Conference on Signals, Systems and Computers, ACSSC 2024 In Conference Record p.822-826
Abstract

Hardware distortion in large intelligent surfaces (LISs) may limit their performance when scaling up such systems. It is of great importance to model the non-ideal effects in their transceivers to study the hardware distortions that can affect their performance. Therefore, we have focused on modeling and studying the effects of nonlinear RX-chains in LISs. We first derive expressions for SNDR of a LIS with a memory-less polynomial-based model at its RX-chains. Then we propose a simplified double-parameter exponential model for the distortion power and show that compared to the polynomial based model, the exponential model can improve the analytical tractability for SNDR optimization problems. In particular, we consider a panel selection... (More)

Hardware distortion in large intelligent surfaces (LISs) may limit their performance when scaling up such systems. It is of great importance to model the non-ideal effects in their transceivers to study the hardware distortions that can affect their performance. Therefore, we have focused on modeling and studying the effects of nonlinear RX-chains in LISs. We first derive expressions for SNDR of a LIS with a memory-less polynomial-based model at its RX-chains. Then we propose a simplified double-parameter exponential model for the distortion power and show that compared to the polynomial based model, the exponential model can improve the analytical tractability for SNDR optimization problems. In particular, we consider a panel selection optimization problems in a panel-based LIS scenario and show that the proposed model enables us to derive two closed-form sub-optimal solutions for panel selection, and can be a favorable alternative to high-order polynomial models in terms of computation complexity, especially for theoretical works on hardware distortion in multiple-input multiple-output (MIMO) and LIS systems. Numerical results show that the sub-optimal closed-form solutions have a near-optimal performance in terms of SNDR compared to the global optimum found by high-complexity heuristic search methods.

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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
keywords
Hardware distortion, Large intelligent surface, MIMO, Panel selection
host publication
2024 58th Asilomar Conference on Signals, Systems, and Computers
series title
Conference Record
pages
5 pages
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
conference name
58th Asilomar Conference on Signals, Systems and Computers, ACSSC 2024
conference location
Hybrid, Pacific Grove, United States
conference dates
2024-10-27 - 2024-10-30
external identifiers
  • scopus:105002694613
ISSN
1058-6393
ISBN
979-8-3503-5405-8
979-8-3503-5406-5 (print-on-demand)
DOI
10.1109/IEEECONF60004.2024.10942661
language
English
LU publication?
yes
id
7b187ffc-74d9-4107-bbd5-f399d6c3a83c
date added to LUP
2025-08-17 19:13:29
date last changed
2025-09-28 23:46:46
@inproceedings{7b187ffc-74d9-4107-bbd5-f399d6c3a83c,
  abstract     = {{<p>Hardware distortion in large intelligent surfaces (LISs) may limit their performance when scaling up such systems. It is of great importance to model the non-ideal effects in their transceivers to study the hardware distortions that can affect their performance. Therefore, we have focused on modeling and studying the effects of nonlinear RX-chains in LISs. We first derive expressions for SNDR of a LIS with a memory-less polynomial-based model at its RX-chains. Then we propose a simplified double-parameter exponential model for the distortion power and show that compared to the polynomial based model, the exponential model can improve the analytical tractability for SNDR optimization problems. In particular, we consider a panel selection optimization problems in a panel-based LIS scenario and show that the proposed model enables us to derive two closed-form sub-optimal solutions for panel selection, and can be a favorable alternative to high-order polynomial models in terms of computation complexity, especially for theoretical works on hardware distortion in multiple-input multiple-output (MIMO) and LIS systems. Numerical results show that the sub-optimal closed-form solutions have a near-optimal performance in terms of SNDR compared to the global optimum found by high-complexity heuristic search methods.</p>}},
  author       = {{Sheikhi, Ashkan and Alegría, Juan Vidal and Edfors, Ove}},
  booktitle    = {{2024 58th Asilomar Conference on Signals, Systems, and Computers}},
  isbn         = {{979-8-3503-5405-8}},
  issn         = {{1058-6393}},
  keywords     = {{Hardware distortion; Large intelligent surface; MIMO; Panel selection}},
  language     = {{eng}},
  pages        = {{822--826}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  series       = {{Conference Record}},
  title        = {{Hardware distortion modeling for panel selection in large intelligent surfaces}},
  url          = {{http://dx.doi.org/10.1109/IEEECONF60004.2024.10942661}},
  doi          = {{10.1109/IEEECONF60004.2024.10942661}},
  year         = {{2024}},
}