Near-Field Localization With Extremely Large Scale Antenna Arrays in the Presence of Mutual Coupling

Extremely large scale antenna arrays (ELAAs) will be a key technology in sixth-generation (6G) wireless communication systems. Due to the large near-field region of ELAAs, sources can easily fall within this area. Hence, a near-field localization algorithm that accounts for the electromagnetic effects of ELAA elements, such as mutual coupling (MC), is essential for proper 6G wireless communication systems design. The three-dimensional (3D) multiple signal classification (MUSIC) algorithm can be used to estimate the near-field source location in the presence of MC. However, this method suffers from a high computational load due to the requirement to perform 3D-based search steps. Recently, to address this issue, an iterative method based on an oblique projection operator (IMOP) has been presented. However, IMOP's computational load can still be high, particularly for ELAA-related scenarios. In this paper, we address this issue by using one sub-array of ELAA which holds far-field assumptions to estimate the direction of arrival (DOA). The DOA estimation relies on an one-dimensional (1D) MUSIC-based algorithm, drastically reducing the computational load. Then, the MC coefficients are calculated using the estimated DOAs. Finally, another 1D MUSIC step is used to estimate the ranges corresponding to the estimated DOA and MC coefficients. Our representative simulation results verify the superiority of the proposed near-field source localization in the presence of MC in terms of computational load, while offering comparable accuracy with the IMOP method.

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Publication Details

Published
2025-03-30
DOI
https://doi.org/10.23919/eucap63536.2025.10999349
Citations
1
Primary Topic
Antenna Design and Optimization
Type
article
Field-Weighted Citation Impact
4.99
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article

Near-Field Localization With Extremely Large Scale Antenna Arrays in the Presence of Mutual Coupling

Anvar Tukmanov, Okan Yurduseven, George C. Alexandropoulos, Amir Masoud Molaei et al.
1 citations
Antenna Design and Optimization
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article

Near-Field Localization With Extremely Large Scale Antenna Arrays in the Presence of Mutual Coupling

Anvar Tukmanov, Okan Yurduseven, George C. Alexandropoulos, Amir Masoud Molaei, Zohreh Ebadi, Muhammad Ali Babar Abbasi, Simon L. Cotton
article en
1 citations

Abstract

Extremely large scale antenna arrays (ELAAs) will be a key technology in sixth-generation (6G) wireless communication systems. Due to the large near-field region of ELAAs, sources can easily fall within this area. Hence, a near-field localization algorithm that accounts for the electromagnetic effects of ELAA elements, such as mutual coupling (MC), is essential for proper 6G wireless communication systems design. The three-dimensional (3D) multiple signal classification (MUSIC) algorithm can be used to estimate the near-field source location in the presence of MC. However, this method suffers from a high computational load due to the requirement to perform 3D-based search steps. Recently, to address this issue, an iterative method based on an oblique projection operator (IMOP) has been presented. However, IMOP's computational load can still be high, particularly for ELAA-related scenarios. In this paper, we address this issue by using one sub-array of ELAA which holds far-field assumptions to estimate the direction of arrival (DOA). The DOA estimation relies on an one-dimensional (1D) MUSIC-based algorithm, drastically reducing the computational load. Then, the MC coefficients are calculated using the estimated DOAs. Finally, another 1D MUSIC step is used to estimate the ranges corresponding to the estimated DOA and MC coefficients. Our representative simulation results verify the superiority of the proposed near-field source localization in the presence of MC in terms of computational load, while offering comparable accuracy with the IMOP method.

BT Group (United Kingdom) (GB), National and Kapodistrian University of Athens (GR)
Openalex Percentile: Top 6%
Antenna Design and Optimization
4.99
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