Localization Coverage Analysis of THz Communication Systems with a 3D Array

Zheng, Pinjun; Ballal, Tarig; Chen, Hui; Wymeersch, Henk; Al-Naffouri, Tareq Y.

doi:10.1109/globecom48099.2022.10000653

Cited by 3 publications

(4 citation statements)

References 49 publications

(86 reference statements)

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“…To the best of the authors' knowledge, there is still a lack of work exploring the spatial structure of the SAs (i.e., 3D array) in an AOSA system, which is expected to enhance the connectivity and improve the coverage w.r.t. both communication and localization key performance indicators (KPIs) [26].…”

Section: Introductionmentioning

confidence: 99%

Coverage Analysis of Joint Localization and Communication in THz Systems With 3D Arrays

Zheng,

Ballal,

Chen

et al. 2024

IEEE Trans. Wireless Commun.

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As a key enabler of Terahertz (THz)-based wireless technologies, large-scale multiple-input-multiple-output systems are well known for their advantages in both communication and localization. Contrary to existing works that mostly focus on planar arrays, this paper first explores the potential of threedimensional (3D) spatial array structures in joint localization and communication coverage enhancement. We consider a THzband wireless system where a user is equipped with a 3D array receiving downlink far-field signals from multiple base stations with known positions and orientations over Rician fading channels. First, we derive the constrained Cramér-Rao bound (CCRB) for the localization (i.e., position and orientation estimation) performance, based on which we define the localization coverage metrics. Then, we derive the communication key performance indicators (KPIs) including instantaneous signal-to-noise ratio, outage probability, and ergodic capacity, and define the corresponding coverage metrics. To facilitate localization applications using 3D arrays, a maximum likelihood-based algorithm for joint user equipment (UE) position and orientation estimation is proposed, which is initialized by a least squares-based solution.Our numerical results show that the 3D array configuration offers overall higher coverage than the planar array w.r.t. both localization and communication KPIs, although with minor performance loss in certain UE positions and orientations. The proposed localization algorithm is also verified to be efficient in simulations as it attains the derived CCRB.

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Section: Introductionmentioning

confidence: 99%

Coverage Analysis of Joint Localization and Communication in THz Systems With 3D Arrays

Zheng,

Ballal,

Chen

et al. 2024

IEEE Trans. Wireless Commun.

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“…User equipment (UE) location estimation is a breakthrough technology in emerging 5G [1][2][3][4], beyond 5G (B5G), and 6G [5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23] Ultra-Dense Networks (UDNs) [24,25]. In [1], a review of the UE location technologies, using 5G gNodeB (gNB) infrastructure, showed meter positioning accuracy.…”

Section: Introductionmentioning

confidence: 99%

“…This is due to the new role of positioning not only as a service of communication networks, but also as an auxiliary means of solving the problems of network organization at the three lower OSI levels. In connection with the ongoing convergence of info-communication and positioning services, provided by the infrastructure of the communication networks of the 5G/B5G/6G networks [5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23], there is reason to believe that the approach of the gNB topology search, based on DOP criteria, deserves attention and can be used for networks of the mmWave and terahertz range, where the density of gNB and UE transceivers will exceed one device per square meter.…”

Section: Introductionmentioning

confidence: 99%

“…An analysis of open foreign sources makes it possible to point out network positioning technologies as a tool for solving problems of network organization in general [5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23], as well as for finding UE locations in particular. According to 3GPP specifications [36][37][38][39][40], the positioning service area should provide sub-meter 3D UE location estimation both in the horizontal and vertical planes; thus, DOP criteria minimization is of great importance.…”

Section: Introductionmentioning

confidence: 99%

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Algorithm for Topology Search Using Dilution of Precision Criterion in Ultra-Dense Network Positioning Service Area

Fokin

Koucheryavy

2023

Mathematics

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User equipment (UE) location estimation in emerging 5G/B5G/6G Ultra-Dense Networks (UDNs) is a breakthrough technology in future wireless info-communication ecosystems. Apart from communication aspects, network infrastructure densification promises significant improvement in UE positioning accuracy. Unlike networks of previous generations, an increased number of gNodeBs (gNBs) per unit area and/or volume in UDNs allows to perform measurements for UE positioning only with those base stations whose topologies are most suitable from the geometric point of view. Quantitative measurements of gNB topology suitability include horizontal (HDOP), vertical (VDOP), and position (PDOP) dilution of the precision (DOP) criteria on the plane, in height, and in space, respectively. In the current work, we formalize a set of methods for gNB topology search using time of arrival (TOA), time difference of arrival (TDOA), angle of arrival (AOA), and combined TOA–AOA and TDOA-AOA measurements. The background of the topology search using DOP criteria is a significantly increased number of gNBs per unit volume in UDNs. Based on a simulation, we propose a novel approach for a topology search in a positioning service area, resulting in a PDOP less than one for the Gazprom Arena with only five gNBs. The contribution of the current research includes algorithm and software for an iterative search of all possible gNB and UE locations in space, minimizing UE geometric DOP. The practical application of the algorithm is the gNB topology substantiation for the given positioning scenarios in 5G/B5G/6G UDNs.

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Integrated Communication, Localization, Sensing and Synchronization in 6G Cognitive Wireless Networks

Volgushev,

Fokin

2024

2024 Systems of Signal Synchronization, Generating and Processing in Telecommunications (SYNCHROINFO)

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Localization Coverage Analysis of THz Communication Systems with a 3D Array

Cited by 3 publications

References 49 publications

Coverage Analysis of Joint Localization and Communication in THz Systems With 3D Arrays

Coverage Analysis of Joint Localization and Communication in THz Systems With 3D Arrays

Algorithm for Topology Search Using Dilution of Precision Criterion in Ultra-Dense Network Positioning Service Area

Integrated Communication, Localization, Sensing and Synchronization in 6G Cognitive Wireless Networks

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