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Deployment Strategy for Indoor Distributed MIMO System

Zhang, Yujie LU orcid ; Alegria, Juan Vidal LU orcid ; Flordelis, Jose ; Bengtsson, Erik L. and Edfors, Ove LU orcid (2026) In IEEE Open Journal of Signal Processing 7. p.305-313
Abstract

The physical placement of antennas is a design factor for Distributed Multiple-Input Multiple-Output (D-MIMO) systems, but finding the optimal layout is a computationally intensive, non-convex problem. Prior research often addresses this by directly optimizing the coordinates of each distributed panels using complex numerical techniques, such as convex relaxation or iterative algorithms. While viable, these methods can be computationally demanding and offer limited insight into the structural properties of optimal deployments. In contrast, this paper introduces a structured, parametric optimization framework. We constrain the panel deployment to a lattice, reducing the high-dimensional problem to optimizing a few parameters that define... (More)

The physical placement of antennas is a design factor for Distributed Multiple-Input Multiple-Output (D-MIMO) systems, but finding the optimal layout is a computationally intensive, non-convex problem. Prior research often addresses this by directly optimizing the coordinates of each distributed panels using complex numerical techniques, such as convex relaxation or iterative algorithms. While viable, these methods can be computationally demanding and offer limited insight into the structural properties of optimal deployments. In contrast, this paper introduces a structured, parametric optimization framework. We constrain the panel deployment to a lattice, reducing the high-dimensional problem to optimizing a few parameters that define the lattice's overall scale and shape. Through numerical simulations, our method is shown to perform nearly indistinguishable from that achieved by a highly complex benchmark, while it outperforms standard approaches like Majorization-Minimizing-Lloyd's algorithm (MM-Lloyd). Furthermore, we identify that a simple, non-optimized, evenly spaced grid can achieve 96% of the benchmark's performance, offering a highly efficient and practical heuristic.

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author
; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
capacity, Distributed MIMO, non-convex optimization, panel deployment
in
IEEE Open Journal of Signal Processing
volume
7
pages
9 pages
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
external identifiers
  • scopus:105027532576
ISSN
2644-1322
DOI
10.1109/OJSP.2026.3654783
language
English
LU publication?
yes
id
165b9a9c-f015-4559-acdd-fc8329260275
date added to LUP
2026-03-16 15:01:35
date last changed
2026-03-23 15:37:32
@article{165b9a9c-f015-4559-acdd-fc8329260275,
  abstract     = {{<p>The physical placement of antennas is a design factor for Distributed Multiple-Input Multiple-Output (D-MIMO) systems, but finding the optimal layout is a computationally intensive, non-convex problem. Prior research often addresses this by directly optimizing the coordinates of each distributed panels using complex numerical techniques, such as convex relaxation or iterative algorithms. While viable, these methods can be computationally demanding and offer limited insight into the structural properties of optimal deployments. In contrast, this paper introduces a structured, parametric optimization framework. We constrain the panel deployment to a lattice, reducing the high-dimensional problem to optimizing a few parameters that define the lattice's overall scale and shape. Through numerical simulations, our method is shown to perform nearly indistinguishable from that achieved by a highly complex benchmark, while it outperforms standard approaches like Majorization-Minimizing-Lloyd's algorithm (MM-Lloyd). Furthermore, we identify that a simple, non-optimized, evenly spaced grid can achieve 96% of the benchmark's performance, offering a highly efficient and practical heuristic.</p>}},
  author       = {{Zhang, Yujie and Alegria, Juan Vidal and Flordelis, Jose and Bengtsson, Erik L. and Edfors, Ove}},
  issn         = {{2644-1322}},
  keywords     = {{capacity; Distributed MIMO; non-convex optimization; panel deployment}},
  language     = {{eng}},
  pages        = {{305--313}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  series       = {{IEEE Open Journal of Signal Processing}},
  title        = {{Deployment Strategy for Indoor Distributed MIMO System}},
  url          = {{http://dx.doi.org/10.1109/OJSP.2026.3654783}},
  doi          = {{10.1109/OJSP.2026.3654783}},
  volume       = {{7}},
  year         = {{2026}},
}