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Keywords = elevation angle of departure

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29 pages, 3101 KB  
Article
Off-Grid Sparse Bayesian Learning for Channel Estimation and Localization in RIS-Assisted MIMO-OFDM Under NLoS
by Ural Mutlu and Yasin Kabalci
Sensors 2025, 25(13), 4140; https://doi.org/10.3390/s25134140 - 2 Jul 2025
Cited by 2 | Viewed by 2346
Abstract
Reconfigurable Intelligent Surfaces (RISs) are among the key technologies envisaged for sixth-generation (6G) multiple-input multiple-output (MIMO)–orthogonal frequency division multiplexing (OFDM) wireless systems. However, their passive nature and the frequent absence of a line-of-sight (LoS) path in dense urban environments make uplink channel estimation [...] Read more.
Reconfigurable Intelligent Surfaces (RISs) are among the key technologies envisaged for sixth-generation (6G) multiple-input multiple-output (MIMO)–orthogonal frequency division multiplexing (OFDM) wireless systems. However, their passive nature and the frequent absence of a line-of-sight (LoS) path in dense urban environments make uplink channel estimation and localization challenging tasks. Therefore, to achieve channel estimation and localization, this study models the RIS-mobile station (MS) channel as a double-sparse angular structure and proposes a hybrid channel parameter estimation framework for RIS-assisted MIMO-OFDM systems. In the hybrid framework, Simultaneous Orthogonal Matching Pursuit (SOMP) first estimates coarse angular supports. The coarse estimates are refined by a novel refinement stage employing a Variational Bayesian Expectation Maximization (VBEM)-based Off-Grid Sparse Bayesian Learning (OG-SBL) algorithm, which jointly updates azimuth and elevation offsets via Newton-style iterations. An Angle of Arrival (AoA)–Angle of Departure (AoD) matching algorithm is introduced to associate angular components, followed by a 3D localization procedure based on non-LoS (NLoS) multipath geometry. Simulation results show that the proposed framework achieves high angular resolution; high localization accuracy, with 97% of the results within 0.01 m; and a channel estimation error of 0.0046% at 40 dB signal-to-noise ratio (SNR). Full article
(This article belongs to the Special Issue Communication, Sensing and Localization in 6G Systems)
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12 pages, 462 KB  
Communication
Adaptive DCS-SOMP for Localization Parameter Estimation in 5G Networks
by Paulo Francisco da Conceição and Flávio Geraldo Coelho Rocha
Sensors 2023, 23(22), 9073; https://doi.org/10.3390/s23229073 - 9 Nov 2023
Cited by 3 | Viewed by 1777
Abstract
In this work, we model a 5G downlink channel using millimeter-wave (mmWave) and massive Multiple-Input Multiple-Output (mMIMO) technologies, considering the following localization parameters: Time of Arrival (TOA), Two-Dimensional Angle of Departure (2D-AoD), and Two-Dimensional Angle of Arrival (2D-AoA), both encompassing azimuth and elevation. [...] Read more.
In this work, we model a 5G downlink channel using millimeter-wave (mmWave) and massive Multiple-Input Multiple-Output (mMIMO) technologies, considering the following localization parameters: Time of Arrival (TOA), Two-Dimensional Angle of Departure (2D-AoD), and Two-Dimensional Angle of Arrival (2D-AoA), both encompassing azimuth and elevation. Our research focuses on the precise estimation of these parameters within a three-dimensional (3D) environment, which is crucial in Industry 4.0 applications such as smart warehousing. In such scenarios, determining the device localization is paramount, as products must be handled with high precision. To achieve these precise estimations, we employ an adaptive approach built upon the Distributed Compressed Sensing—Subspace Orthogonal Matching Pursuit (DCS-SOMP) algorithm. We obtain better estimations using an adaptive approach that dynamically adapts the sensing matrix during each iteration, effectively constraining the search space. The results demonstrate that our approach outperforms the traditional method in terms of accuracy, speed to convergence, and memory use. Full article
(This article belongs to the Special Issue Advanced Localization and Motion Tracking with Dense Wireless Networks)
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21 pages, 5363 KB  
Article
Practical 3-D Beam Pattern Based Channel Modeling for Multi-Polarized Massive MIMO Systems
by Saeid Aghaeinezhadfirouzja, Hui Liu and Ali Balador
Sensors 2018, 18(4), 1186; https://doi.org/10.3390/s18041186 - 12 Apr 2018
Cited by 3 | Viewed by 6853
Abstract
In this paper, a practical non-stationary three-dimensional (3-D) channel models for massive multiple-input multiple-output (MIMO) systems, considering beam patterns for different antenna elements, is proposed. The beam patterns using dipole antenna elements with different phase excitation toward the different direction of travels (DoTs) [...] Read more.
In this paper, a practical non-stationary three-dimensional (3-D) channel models for massive multiple-input multiple-output (MIMO) systems, considering beam patterns for different antenna elements, is proposed. The beam patterns using dipole antenna elements with different phase excitation toward the different direction of travels (DoTs) contributes various correlation weights for rays related towards/from the cluster, thus providing different elevation angle of arrivals (EAoAs) and elevation angle of departures (EAoDs) for each antenna element. These include the movements of the user that makes our channel to be a non-stationary model of clusters at the receiver (RX) on both the time and array axes. In addition, their impacts on 3-D massive MIMO channels are investigated via statistical properties including received spatial correlation. Additionally, the impact of elevation/azimuth angles of arrival on received spatial correlation is discussed. Furthermore, experimental validation of the proposed 3-D channel models on azimuth and elevation angles of the polarized antenna are specifically evaluated and compared through simulations. The proposed 3-D generic models are verified using relevant measurement data. Full article
(This article belongs to the Special Issue Smart Vehicular Mobile Sensing)
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13 pages, 2977 KB  
Article
The Impact of Antenna Height on 3D Channel: A Ray Launching Based Analysis
by Qi Hong, Jiliang Zhang, Hui Zheng, Hao Li, Haonan Hu, Baoling Zhang, Zhihua Lai and Jie Zhang
Electronics 2018, 7(1), 2; https://doi.org/10.3390/electronics7010002 - 3 Jan 2018
Cited by 13 | Viewed by 5544
Abstract
Three-dimensional (3D) multi-input-multi-output (MIMO) is one of the enabling technologies for next-generation mobile communication. As the elevation angle in the 3D MIMO channel model might vary against the height of the base station (BS) antenna, it should be considered within channel modeling. In [...] Read more.
Three-dimensional (3D) multi-input-multi-output (MIMO) is one of the enabling technologies for next-generation mobile communication. As the elevation angle in the 3D MIMO channel model might vary against the height of the base station (BS) antenna, it should be considered within channel modeling. In this paper, the impact of antenna height on the channel characteristics of the 3D MIMO channel is investigated by using the intelligent ray launching algorithm (IRLA). Three typical street scenarios, i.e., the straight street, the forked road, and the crossroad, are selected as benchmarks. The joint and marginal probability density functions (PDFs) of both the elevation angle of departure (EAoD) and the elevation angle of arrival (EAoA) are obtained through simulations. Moreover, the elevation angle spread (AS) and the elevation delay spread (DS) under various antenna heights are jointly discussed. Simulation results show that the characteristics of the PDFs of EAoD will vary under different street scenarios. It is observed that in order to obtain the maximum or minimum value of the AS and the DS, the BS antenna should be deployed at half of the building height. Full article
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