Article
Computer Science, Information Systems
Baghdad Hadji, Abdeldjalil Aissa-El-Bey, Lamya Fergani, Mustapha Djeddou
Summary: This paper proposes an iterative method based on alternating minimization to design the optimal sensing matrix for better compressed sensing recovery performance. By formulating the optimization design problem as the nearest Kronecker product problem, the best hybrid precoders and combiners are jointly derived. Compared to existing schemes, the proposed method achieves better channel estimation accuracy and spectral efficiency.
Article
Engineering, Electrical & Electronic
Jianwei Zhao, Jun Liu, Feifei Gao, Weimin Jia, Wei Zhang
Summary: This paper investigates the channel effects in UAV communications and proposes a new channel tracking method that can effectively reduce channel training overhead. Various simulation results are provided to verify the effectiveness of the proposed methods.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2021)
Article
Engineering, Electrical & Electronic
Pengcheng Zhu, Huixin Lin, Jiamin Li, Dongming Wang, Xiaohu You
Summary: This paper investigates the channel estimation problem in millimeter-wave (mmWave) multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems with hybrid structures. A beamspace multiple signal classification (MUSIC) algorithm is proposed for mmWave wideband channels to simultaneously estimate the angles of arrival (AOAs), angles of departure (AODs), and transmission delays. A multi-spectral peak search method is designed to search for multiple spectral peaks on the MUSIC spatial spectrum more quickly and accurately, overcoming the high complexity of traditional spectral peak search methods. The proposed channel estimator is also extended to actual systems equipped with uniform planar arrays (UPAs). Finally, the performance of the proposed channel parameter estimator is evaluated by deriving the Cramer-Rao bound (CRB) results of these channel parameters. Simulation results demonstrate the greatly high channel estimation accuracy of the proposed channel estimator.
IEEE TRANSACTIONS ON COMMUNICATIONS
(2023)
Article
Computer Science, Information Systems
Weiqiang Tong, Wenjun Xu, Fengyu Wang, Jin Shang, Miao Pan, Jiaru Lin
Summary: This letter proposes a two-step orthogonal matching pursuit method based on deep learning compressed sensing for channel estimation in mmWave massive MIMO systems. The proposed method achieves superior performance compared to existing methods and works robustly in low SNR regimes with a small amount of training data.
IEEE WIRELESS COMMUNICATIONS LETTERS
(2022)
Article
Engineering, Electrical & Electronic
Suraj Srivastava, Ch Suraj Kumar Patro, Aditya K. Jagannatham, Lajos Hanzo
Summary: Sparse Bayesian learning and group-sparse Bayesian learning techniques are utilized to exploit the angular sparsity of mmWave channel, improving channel estimation performance and reducing error. A low complexity version and online channel estimation method are proposed, aiming to decrease processing delay. Additionally, a hybrid transmit precoder and receive combiner are designed for enhanced system performance.
IEEE TRANSACTIONS ON COMMUNICATIONS
(2021)
Article
Telecommunications
Yi Song, Chuanzong Zhang, Fabio Saggese, Xinhua Lu, Zhongyong Wang, Zhengyu Zhu
Summary: In this study, we propose the Bernoulli two-state Gaussian mixture (B-TSGM) probability model to characterize the angle-delay domain (ADD) channel of the massive MIMO-OFDM system. We design an HMP-B-TSGM channel estimation algorithm based on the hybrid message passing (HMP) rule under the structured turbo-compressed sensing (STCS) framework. Simulation results demonstrate that the proposed model effectively captures the channel characteristics and the algorithm outperforms state-of-the-art methods with similar complexity.
IEEE COMMUNICATIONS LETTERS
(2023)
Article
Engineering, Electrical & Electronic
Yuxing Lin, Shi Jin, Michail Matthaiou, Xiaohu You
Summary: A method for channel estimation in MIMO-OFDM systems assisted by intelligent reconfigurable surfaces (IRSs) is proposed in this paper. By utilizing a hybrid IRS architecture and exploiting the sparse characteristics of high-frequency propagation, the multipath channel parameters are successfully estimated. Simulation results demonstrate that the proposed schemes outperform traditional methods in terms of accuracy, robustness, and complexity.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
(2021)
Article
Engineering, Electrical & Electronic
Xiaofeng Liu, Wenjin Wang, Xinrui Gong, Xiao Fu, Xiqi Gao, Xiang-Gen Xia
Summary: This paper investigates uplink channel estimation for massive MIMO-OFDM systems with UPA antennas. It presents a triple beam-based channel model and a 3D-MRF probability model to capture channel sparsity. It also proposes a structured hybrid message passing algorithm to improve estimation accuracy with low complexity.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Engineering, Electrical & Electronic
Asmaa Abdallah, Abdulkadir Celik, Mohammad M. Mansour, Ahmed M. Eltawil
Summary: This paper proposes data-driven and compressive sensing based approaches to estimate both frequency-flat and frequency-selective cascaded channels of RIS-assisted multi-user millimeter-wave large MIMO systems with limited training overhead. The proposed algorithms exploit the common sparsity property among different subcarriers and the double-structured sparsity property of the angular cascaded channel matrices. Simulation results show that the proposed scheme achieves lower pilot overhead and significantly reduces complexity compared to existing schemes.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
(2023)
Article
Computer Science, Information Systems
Mohamed Alouzi, Faisal Al-Kamali, Claude D'amours, Francois Chan
Summary: This paper introduces a new hybrid array (HA) architecture for millimeter-wave (mmWave) MIMO systems, aiming to achieve a balance between spectral efficiency, cost, and power consumption. The proposed HA architecture utilizes antenna grouping and connection methods to achieve higher spectral efficiency, cost reduction, and power reduction compared to conventional designs.
Article
Engineering, Electrical & Electronic
Xiao Gong, Wei Chen, Lei Sun, Jie Chen, Bo Ai
Summary: This paper focuses on the problem of downlink supervised channel estimation for millimeter wave three-dimensional multiple-input multiple-output orthogonal frequency division multiplexing (mmWave 3D MIMO-OFDM) systems with uniform rectangular arrays (URAs) at both the transmitter and the receiver. A fast ESPRIT-based Vandermonde-structured tensor decomposition method is proposed to estimate the channel parameters, including angles of arrival and departure (AoAs/AoDs), delays, and path gains, by treating the mmWave channel as a low-rank higher-order tensor. The proposed method achieves higher estimation accuracy and saves up to 87% of computing time compared to the current best iterative algorithm in experiments.
IEEE TRANSACTIONS ON SIGNAL PROCESSING
(2023)
Article
Computer Science, Information Systems
Yushan Liu, Shun Zhang, Feifei Gao, Jie Tang, Octavia A. Dobre
Summary: This study proposes a cascaded channel estimation framework for RIS-assisted mmWave communications, taking into account the wideband effect and using the Newtonized orthogonal matching pursuit algorithm for channel parameter detection. The Cramer-Rao lower bound is introduced to evaluate the channel estimation performance. Numerical results demonstrate the effectiveness of the proposed channel estimation scheme.
IEEE WIRELESS COMMUNICATIONS LETTERS
(2021)
Article
Engineering, Electrical & Electronic
Weicong Chen, Yu Han, Shi Jin, Huan Sun
Summary: This study focuses on efficiently reconstructing and tracking time drifting multiband channels in a hybrid analog/digital architecture for time division duplex (TDD) mmWave multiple-input-multiple-output systems. By introducing an efficient multiband channel reconstruction scheme and a beam training-based algorithm, the central sub-band channel and side sub-band channels can be accurately estimated and reconstructed, while a rotated beam-based channel tracking algorithm is developed to keep the channel state information accurate in slightly drifting channels.
IEEE TRANSACTIONS ON COMMUNICATIONS
(2021)
Article
Computer Science, Hardware & Architecture
Olutayo O. Oyerinde, Adam Flizikowski, Tomasz Marciniak
Summary: This paper proposes two new channel estimation techniques for wideband channels in mmWave Massive MIMO systems. The POLS-based estimator achieves a balance between performance and computational complexity, making it the optimal choice.
COMPUTERS & ELECTRICAL ENGINEERING
(2022)
Article
Engineering, Electrical & Electronic
Zhen Chen, Jie Tang, Xiu Yin Zhang, Daniel Ka Chun So, Shi Jin, Kai-Kit Wong
Summary: This paper proposes a compressive channel estimation technique for intelligent reflecting surface (IRS)-assisted millimeter wave (mmWave) multi-input and multi-output (MIMO) system. By exploiting the sparsity of mmWave channels, the channel estimation problem is converted into a sparse signal recovery problem and solved using a hybrid multiobjective evolutionary paradigm. Simulation results demonstrate that the proposed method achieves competitive error performance under a wide range of simulation settings.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
(2022)
