scholarly journals GAMP-SBL Based Channel Estimation for Millimeter-Wave MIMO Systems

2021 ◽  
Author(s):  
Jianfeng Shao ◽  
Xianpeng Wang ◽  
Xiang Lan ◽  
Zhiguang Han ◽  
Ting Su
Keyword(s):  
Channel Estimation ◽  
Millimeter Wave ◽  
Message Passing ◽  
Mimo Systems ◽  
Mimo System ◽  
Estimation Algorithm ◽  
Mimo Channel ◽  
Estimation Methods ◽  
Estimation Accuracy ◽  
Signal Recovery

Abstract Based on the finite scattering characters of the millimeter-wave multiple-input multiple-output (mmWave MIMO) channel, the mmWave channel estimation problem can be considered as a sparse signal recovery problem. However, most traditional channel estimation methods depend on grid search, which may lead to considerable precision loss. To improve the channel estimation accuracy, we propose a high-precision two-stage millimeter-wave MIMO system channel estimation algorithm. Since the traditional expectation-maximization based sparse Bayesian learning (EM-SBL) algorithm can be applied to handle this problem, however, it spends lots of time to calculate the E-step which needs to compute the inversion of a high dimensional matrix. To avoid the high computation of matrix inversion, we combine damp generalized approximate message passing (DGAMP) with the E-step in SBL. We then improve a refined algorithm to handle the dictionary matrix mismatching problem in sparse representation. Numerical simulations show that the estimation time of the proposed algorithm is greatly reduced compared with the traditional SBL algorithm and better estimation performance is obtained at the same time.

scholarly journals GAMP-SBL-based channel estimation for millimeter-wave MIMO systems

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Jianfeng Shao ◽  
Xianpeng Wang ◽  
Xiang Lan ◽  
Zhiguang Han ◽  
Ting Su
Keyword(s):  
Channel Estimation ◽  
Millimeter Wave ◽  
Mimo Systems ◽  
Learning Algorithm ◽  
Mimo System ◽  
Estimation Algorithm ◽  
Mimo Channel ◽  
Estimation Methods ◽  
Estimation Accuracy ◽  
Signal Recovery

AbstractBased on the finite scattering characters of the millimeter-wave multiple-input multiple-output (MIMO) channel, the mmWave channel estimation problem can be considered as a sparse signal recovery problem. However, most traditional channel estimation methods depend on grid search, which may lead to considerable precision loss. To improve the channel estimation accuracy, we propose a high-precision two-stage millimeter-wave MIMO system channel estimation algorithm. Since the traditional expectation–maximization-based sparse Bayesian learning algorithm can be applied to handle this problem, it spends lots of time to calculate the E-step which needs to compute the inversion of a high-dimensional matrix. To avoid the high computation of matrix inversion, we combine damp generalized approximate message passing with the E-step in SBL. We then improve a refined algorithm to handle the dictionary matrix mismatching problem in sparse representation. Numerical simulations show that the estimation time of the proposed algorithm is greatly reduced compared with the traditional SBL algorithm and better estimation performance is obtained at the same time.

scholarly journals Grouping-Based Channel Estimation and Tracking for Millimeter Wave Massive MIMO Systems

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Rui Yin ◽  
Xin Zhou ◽  
Wei Qi ◽  
Celimuge Wu ◽  
Yunlong Cai
Keyword(s):  
Computational Complexity ◽  
Channel Estimation ◽  
Millimeter Wave ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Mimo System ◽  
Closed Form Solution ◽  
Network Capacity ◽  
Base Station ◽  
Estimation Accuracy

Although the millimeter wave (mmWave) massive multiple-input and multiple-output (MIMO) system can potentially boost the network capacity for future communications, the pilot overhead of the system in practice will greatly increase, which causes a significant decrease in system performance. In this paper, we propose a novel grouping-based channel estimation and tracking approach to reduce the pilot overhead and computational complexity while improving the estimation accuracy. Specifically, we design a low-complexity iterative channel estimation and tracking algorithm by fully exploiting the sparsity of mmWave massive MIMO channels, where the signal eigenvectors are estimated and tracked based on the received signals at the base station (BS). With the recovered signal eigenvectors, the celebrated multiple-signal classification (MUSIC) algorithm can be employed to estimate the direction of arrival (DoA) angles and the path amplitude for the user terminals (UTs). To improve the estimation accuracy and accelerate the tracking speed, we develop a closed-form solution for updating the step-size in the proposed iterative algorithm. Furthermore, a grouping method is proposed to reduce the number of sharing pilots in the scenario of multiple UTs to shorten the pilot overhead. The computational complexity of the proposed algorithm is analyzed. Simulation results are provided to verify the effectiveness of the proposed schemes in terms of the estimation accuracy, tracking speed, and overhead reduction.

scholarly journals Channel Estimation for Broadband Millimeter Wave MIMO Systems Based on High-Order PARALIND Model

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Ting Jiang ◽  
Maozhong Song ◽  
Xiaorong Zhu ◽  
Xu Liu
Keyword(s):  
Channel Estimation ◽  
Millimeter Wave ◽  
Mimo Systems ◽  
Model Simulation ◽  
Path Loss ◽  
Estimation Algorithm ◽  
Multipath Channels ◽  
High Order ◽  
Propagation Path ◽  
Necessary Condition

Channel state information (CSI) is important to improve the performance of wireless transmission. However, the problems of high propagation path loss, multipath, and frequency selective fading make it difficult to obtain the CSI in broadband millimeter-wave (mmWave) system. Based on the inherent multidimensional structure of mmWave multipath channels and the correlation between channel dimensions, mmWave multiple input multiple output (MIMO) channels are modelled as high-order parallel profiles with linear dependence (PARALIND) model in this paper, and a new PARALIND-based channel estimation algorithm is proposed for broadband mmWave system. Due to the structural property of PARALIND model, the proposed algorithm firstly separates the multipath channels of different scatterers by PARALIND decomposition and then estimates the channel parameters from the factor matrices decomposed from the model based on their structures. Meanwhile, the performance of mmWave channel estimation is analysed theoretically. A necessary condition for channel parameter estimation is given based on the uniqueness principle of PARALIND model. Simulation results show that the proposed algorithm performs better than traditional compressive sensing-based channel estimation algorithms.

scholarly journals On the Performance of Efficient Channel Estimation Strategies for Hybrid Millimeter Wave MIMO System

Entropy ◽  
2020 ◽  
Vol 22 (10) ◽  
pp. 1121
Author(s):  
Prateek Saurabh Srivastav ◽  
Lan Chen ◽  
Arfan Haider Wahla
Keyword(s):  
Channel Estimation ◽  
Millimeter Wave ◽  
Optimization Problem ◽  
Mimo Systems ◽  
Mimo System ◽  
Low Rank ◽  
Potential Candidate ◽  
Alternating Direction ◽  
The Individual ◽  
Joint Channel

Millimeter wave (mmWave) relying upon the multiple output multiple input (MIMO) is a new potential candidate for fulfilling the huge emerging bandwidth requirements. Due to the short wavelength and the complicated hardware architecture of mmWave MIMO systems, the conventional estimation strategies based on the individual exploitation of sparsity or low rank properties are no longer efficient and hence more modern and advance estimation strategies are required to recapture the targeted channel matrix. Therefore, in this paper, we proposed a novel channel estimation strategy based on the symmetrical version of alternating direction methods of multipliers (S-ADMM), which exploits the sparsity and low rank property of channel altogether in a symmetrical manner. In S-ADMM, at each iteration, the Lagrange multipliers are updated twice which results symmetrical handling of all of the available variables in optimization problem. To validate the proposed algorithm, numerous computer simulations have been carried out which straightforwardly depicts that the S-ADMM performed well in terms of convergence as compared to other benchmark algorithms and also able to provide global optimal solutions for the strictly convex mmWave joint channel estimation optimization problem.

ESTIMATION METHODS OF A CHANNEL WITH SPATIAL MODULATION BASED ON CORRELATION

2021 ◽  
pp. 106-110
Author(s):  
О.Н. Чирков
Keyword(s):  
Channel Estimation ◽  
Communication Channel ◽  
Energy Savings ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Spatial Modulation ◽  
Mimo Channel ◽  
Estimation Methods ◽  
Signal Ratio ◽  
Single Stream

Рассматриваются методы оценки канала связи с пространственной модуляцией. Данный вид модуляции представляет собой методику однопотоковой передачи данных с несколькими входами и несколькими выходами (MIMO), при которой одновременно активируется только одна передающая антенна. Пространственная модуляция позволяет добиться полного исключения межканальных помех, а также демонстрирует большую экономию энергии в радиочастотной цепи. Однако, в отличие от многопоточных систем MIMO, оценка канала для пространственной модуляции становится проблемой, поскольку канал MIMO не может быть оценен на одном этапе передачи по единственному потоку. На основании этого факта была предложена новая схема оценки канала, которая использует корреляцию каналов и совместно оценивает каналы для разных передающих антенн. Предложенный метод обеспечивает тот же период оценки, что и многопоточные схемы MIMO. Исследовано изменение количества передаваемых пилот-сигналов при пространственной модуляции как для традиционных, так и для новых методов оценки канала связи. Уравновешивая точность и объем данных, можно достичь оптимального отношения пилот-сигналов для максимальной пропускной способности канала. Результаты моделирования показывают, что новый подход оценки превосходит традиционный метод с гораздо более низким оптимальным коэффициентом количества пилотов The article considers methods for estimating a communication channel with spatial modulation. This type of modulation is a single-stream multiple-input multiple-output (MIMO) technique in which only one transmit antenna is activated at a time. Spatial modulation allows for complete elimination of inter-channel interference, and also demonstrates great energy savings in the RF circuit. However, unlike multi-stream MIMO systems, channel estimation for spatial modulation becomes a problem because a MIMO channel cannot be estimated in a single transmission step on a single stream. Based on this fact, I proposed a new channel estimation scheme that uses channel correlation and jointly estimates channels for different transmit antennas. The proposed method provides the same evaluation period as multithreaded MIMO schemes. The change in the number of transmitted pilot-signals with spatial modulation is investigated for both traditional and new methods of estimation of the communication channel. By balancing accuracy and data volume, an optimal pilot signal ratio can be achieved for maximum channel throughput. Simulation results show that the new scoring approach outperforms the traditional method with a much lower optimal pilot count ratio

scholarly journals Low-Complexity Joint Channel Estimation for Multi-User mmWave Massive MIMO Systems

Electronics ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 301
Author(s):  
Jianhe Du ◽  
Jiaqi Li ◽  
Jing He ◽  
Yalin Guan ◽  
Heyun Lin
Keyword(s):  
Channel Estimation ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Estimation Algorithm ◽  
Step Length ◽  
Low Complexity ◽  
Base Station ◽  
Estimation Accuracy ◽  
Input Multiple Output

For multi-user millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems, the precise acquisition of channel state information (CSI) is a huge challenge. With the increase of the number of antennas at the base station (BS), the traditional channel estimation techniques encounter the problems of pilot training overhead and computational complexity increasing dramatically. In this paper, we develop a step-length optimization-based joint iterative scheme for multi-user mmWave massive MIMO systems to improve channel estimation performance. The proposed estimation algorithm provides the BS with full knowledge of all channel parameters involved in up- and down-links. Compared with existing algorithms, the proposed algorithm has higher channel estimation accuracy with low complexity. Moreover, the proposed scheme performs well even with a small number of training sequences and a large number of users. Simulation results are shown to demonstrate the performance of the proposed channel estimation algorithm.

scholarly journals Improvement of Complexity and Performance of Least Square Based Channel Estimation in MIMO System

2016 ◽  
Vol 1 ◽  
pp. 11
Author(s):  
Anand Kumar Sah ◽  
Arun Kumar Timalsina
Keyword(s):  
Channel Estimation ◽  
Mimo Systems ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Estimation Method ◽  
Vital Role ◽  
Least Square ◽  
Mimo Channel ◽  
Fourth Generation ◽  
Simulation Results

<p>Multiple-input multiple-output (MIMO) systems play a vital role in fourth generation wireless systems to provide advanced data rate. In this paper, a better performance and reduced complexity channel estimation method is proposed for MIMO systems based on matrix factorization. This technique is applied on training based least squares (LS) channel estimation using STBC for performance improvement. Simulation results indicate that the proposed method not only alleviates the performance of MIMO channel estimation but also significantly reduces the complexity caused by matrix inversion. The performance evaluations are validated through computer simulations using MATLAB in terms of bit error rate (BER) for modified LS with LS and MMSE channel estimation techniques. Simulation results show that the BER performance and complexity of the proposed method clearly outperforms the conventional LS channel estimation method.</p><p><em>Journal of Advanced College of Engineering and Management, Vol. 1, 2015</em>, pp. 11-24</p>

scholarly journals Channel Sounding for Multi-User Massive MIMO in Distributed Antenna System Environment

Electronics ◽  
2019 ◽  
Vol 8 (1) ◽  
pp. 36 ◽  
Author(s):  
Seoyoung Yu ◽  
Jeong Woo Lee
Keyword(s):  
Channel Estimation ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Mimo System ◽  
Reference Signal ◽  
Estimation Algorithm ◽  
Antenna System ◽  
Distributed Antenna System ◽  
Distributed Antenna ◽  
Estimation Scheme

We propose a generation scheme for a sounding reference signal (SRS) suitable for supporting a large number of users in massive multi-input multi-output (MIMO) system with a distributed antenna system (DAS) environment. The proposed SRS can alleviate the pilot contamination problem which occurs inherently in the multi-user system due to the limited number of orthogonal sequences. The proposed SRS sequence is generated by applying a well-chosen phase rotation to the conventional LTE/LTE-A SRS sequences without requiring an increased amount of resource usage. We also propose using the correlation-aided channel estimation algorithm as a supplemental scheme to obtain more reliable and refined channel estimation. It is shown that the proposed SRS sequence and the supplemental channel estimation scheme improve significantly the channel estimation performance in multi-user massive MIMO systems.

scholarly journals WSDSBL Method for Wideband Channel Estimation in Millimeter-Wave MIMO Systems with Lens Antenna Array

2020 ◽  
pp. 826-832
Author(s):  
Jicheng Dong ◽  
◽  
Wei Zhang ◽  
Bowen Yang ◽  
Xihong Sang
Keyword(s):  
Channel Estimation ◽  
Millimeter Wave ◽  
Communication Systems ◽  
Bayesian Learning ◽  
Mimo Systems ◽  
Estimation Accuracy ◽  
Sparse Bayesian Learning ◽  
Low Snr ◽  
Estimation Scheme ◽  
Wideband Channel

In millimeter wave (mmWave) communication systems, Channel State Information(CSI) is extremely essential for beamforming. The traditional Successive Support Detection (SSD) algorithm can achieve high wideband channel estimation accuracy, but it only used least square (LS) algorithm to recover the detected channel part, the estimation accuracy is low under low SNR regions. To tackle this problem, in this paper, inspired by the classic Support Detection (SD) channel estimation scheme in narrowband, we propose an efficient Wideband Support Detection Sparse Bayesian Learning (WSDSBL) channel estimation scheme. For every subcarrier, we first detect the support of the wideband beamspace channel of the subcarrier, then we use the Sparse Bayesian Learning (SBL) scheme to recover it. Simulation results show that the proposed WSDSBL channel estimation algorithm is better than conventional wideband channel estimation schemes in MSE performance and achievable sum-rate performance, especially in low SNR regions.

scholarly journals Uplink Sparse Channel Estimation for Hybrid Millimeter Wave Massive MIMO Systems by UTAMP-SBL

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4760
Author(s):  
Shuai Hou ◽  
Yafeng Wang ◽  
Chao Li
Keyword(s):  
Channel Estimation ◽  
Millimeter Wave ◽  
Message Passing ◽  
Massive Mimo ◽  
Communication Systems ◽  
Bayesian Learning ◽  
Mimo Systems ◽  
Complex Signal ◽  
Hybrid Architecture ◽  
Sparse Channel

The compressive sensing (CS)-based sparse channel estimator is recognized as the most effective solution to the excessive pilot overhead in massive MIMO systems. However, due to the complex signal processing in the wireless communication systems, the measurement matrix in the CS-based channel estimation is sometimes “unfriendly” to the channel recovery. To overcome this problem, in this paper, the state-of-the-art sparse Bayesian learning using approximate message passing with unitary transformation (UTAMP-SBL), which is robust to various measurement matrices, is leveraged to address the multi-user uplink channel estimation for hybrid architecture millimeter wave massive MIMO systems. Specifically, the sparsity of channels in the angular domain is exploited to reduce the pilot overhead. Simulation results demonstrate that the UTAMP-SBL is able to achieve effective performance improvement than other competitors with low pilot overhead.

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