RSS Localization in Cell-Free Massive MIMO: Algorithms, Analysis, and Implementation

Jiajun He; Hien Quoc Ngo; Chao Wang; Feng Yin; Hing Cheung So; Hyundong Shin; Michail Matthaiou

doi:10.1109/TWC.2025.3607721

RSS Localization in Cell-Free Massive MIMO: Algorithms, Analysis, and Implementation

Jiajun He
, Hien Quoc Ngo
, Chao Wang
, Feng Yin
, Hing Cheung So
, Hyundong Shin^*
, Michail Matthaiou^*

^*Corresponding author for this work

Department of Electrical Engineering

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

1 Citation (Scopus)

Abstract

Received signal strength (RSS) has been extensively studied for localization purposes, and the distributed nature of cell-free massive multiple-input multiple-output (CF-mMIMO) systems offers a new synergistic avenue for achieving high-precision localization. In this work, Open RAN and software-defined radio are used to realize the central and distributed units of a CF-mMIMO system to acquire the RSS measurements. By analyzing the experimental data, it is revealed that the RSS measured from the first-order reflection path can yield a sufficiently high signal-to-noise ratio for localization, enabling localization even without line-of-sight (LoS) paths. Inspired by this finding, a hybrid localization scheme, that can attain the best accuracy benchmarked by Cramér-Rao lower bound, is proposed to estimate the target position using both LoS and first-order non-line-of-sight RSS measurements. Furthermore, a theoretical framework is established to assess the fundamental limits of RSS-based localization in CF-mMIMO systems, offering a principled guideline for system designers to deploy and design localization systems in real-world scenarios. © 2025 IEEE.

Original language	English
Pages (from-to)	4021-4037
Journal	IEEE Transactions on Wireless Communications
Volume	25
Online published	17 Sept 2025
DOIs	https://doi.org/10.1109/TWC.2025.3607721
Publication status	Published - 2026

Funding

This work was supported by U.K. Engineering and Physical Sciences Research Council (EPSRC) under Grant EP/Y037243/1 and Grant EP/X040569/1. The work of Hien Quoc Ngo was supported in part by U.K. Research and Innovation Future Leaders Fellowships under Grant MR/X010635/1 and in part by the Department for the Economy Northern Ireland through the U.S.–Ireland Research and Development Partnership Program. The work of Hyundong Shin was supported in part by the National Research Foundation of Korea (NRF) Grant funded by Korean Government [Ministry of Science and Information and Communication Technology (MSIT)], South Korea, under Grant RS-2025-00556064; and in part by MSIT through the Information Technology Research Center (ITRC) Support Program supervised by the Institute for Information and Communications Technology Planning and Evaluation (IITP) under Grant IITP-2025-2021-0- 02046. The work of Michail Matthaiou was supported by European Research Council (ERC) through European Union’s Horizon 2020 Research and Innovation Program under Grant 101001331.

Research Keywords

Cell-free massive MIMO
localization
non-line-of-sight
received signal strength
reflection loss

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title = "RSS Localization in Cell-Free Massive MIMO: Algorithms, Analysis, and Implementation",

abstract = "Received signal strength (RSS) has been extensively studied for localization purposes, and the distributed nature of cell-free massive multiple-input multiple-output (CF-mMIMO) systems offers a new synergistic avenue for achieving high-precision localization. In this work, Open RAN and software-defined radio are used to realize the central and distributed units of a CF-mMIMO system to acquire the RSS measurements. By analyzing the experimental data, it is revealed that the RSS measured from the first-order reflection path can yield a sufficiently high signal-to-noise ratio for localization, enabling localization even without line-of-sight (LoS) paths. Inspired by this finding, a hybrid localization scheme, that can attain the best accuracy benchmarked by Cram{\'e}r-Rao lower bound, is proposed to estimate the target position using both LoS and first-order non-line-of-sight RSS measurements. Furthermore, a theoretical framework is established to assess the fundamental limits of RSS-based localization in CF-mMIMO systems, offering a principled guideline for system designers to deploy and design localization systems in real-world scenarios. {\textcopyright} 2025 IEEE.",

keywords = "Cell-free massive MIMO, localization, non-line-of-sight, received signal strength, reflection loss",

author = "Jiajun He and Ngo, \{Hien Quoc\} and Chao Wang and Feng Yin and So, \{Hing Cheung\} and Hyundong Shin and Michail Matthaiou",

year = "2026",

doi = "10.1109/TWC.2025.3607721",

language = "English",

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pages = "4021--4037",

journal = "IEEE Transactions on Wireless Communications",

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TY - JOUR

T1 - RSS Localization in Cell-Free Massive MIMO

T2 - Algorithms, Analysis, and Implementation

AU - He, Jiajun

AU - Ngo, Hien Quoc

AU - Wang, Chao

AU - Yin, Feng

AU - So, Hing Cheung

AU - Shin, Hyundong

AU - Matthaiou, Michail

PY - 2026

Y1 - 2026

N2 - Received signal strength (RSS) has been extensively studied for localization purposes, and the distributed nature of cell-free massive multiple-input multiple-output (CF-mMIMO) systems offers a new synergistic avenue for achieving high-precision localization. In this work, Open RAN and software-defined radio are used to realize the central and distributed units of a CF-mMIMO system to acquire the RSS measurements. By analyzing the experimental data, it is revealed that the RSS measured from the first-order reflection path can yield a sufficiently high signal-to-noise ratio for localization, enabling localization even without line-of-sight (LoS) paths. Inspired by this finding, a hybrid localization scheme, that can attain the best accuracy benchmarked by Cramér-Rao lower bound, is proposed to estimate the target position using both LoS and first-order non-line-of-sight RSS measurements. Furthermore, a theoretical framework is established to assess the fundamental limits of RSS-based localization in CF-mMIMO systems, offering a principled guideline for system designers to deploy and design localization systems in real-world scenarios. © 2025 IEEE.

AB - Received signal strength (RSS) has been extensively studied for localization purposes, and the distributed nature of cell-free massive multiple-input multiple-output (CF-mMIMO) systems offers a new synergistic avenue for achieving high-precision localization. In this work, Open RAN and software-defined radio are used to realize the central and distributed units of a CF-mMIMO system to acquire the RSS measurements. By analyzing the experimental data, it is revealed that the RSS measured from the first-order reflection path can yield a sufficiently high signal-to-noise ratio for localization, enabling localization even without line-of-sight (LoS) paths. Inspired by this finding, a hybrid localization scheme, that can attain the best accuracy benchmarked by Cramér-Rao lower bound, is proposed to estimate the target position using both LoS and first-order non-line-of-sight RSS measurements. Furthermore, a theoretical framework is established to assess the fundamental limits of RSS-based localization in CF-mMIMO systems, offering a principled guideline for system designers to deploy and design localization systems in real-world scenarios. © 2025 IEEE.

KW - Cell-free massive MIMO

KW - localization

KW - non-line-of-sight

KW - received signal strength

KW - reflection loss

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U2 - 10.1109/TWC.2025.3607721

DO - 10.1109/TWC.2025.3607721

M3 - RGC 21 - Publication in refereed journal

SN - 1536-1276

VL - 25

SP - 4021

EP - 4037

JO - IEEE Transactions on Wireless Communications

JF - IEEE Transactions on Wireless Communications

ER -

RSS Localization in Cell-Free Massive MIMO: Algorithms, Analysis, and Implementation

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