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

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.

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

EURASIP Journal on Advances in Signal Processing ◽

10.1186/s13634-021-00792-w ◽

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.

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

10.21203/rs.3.rs-637648/v1 ◽

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.

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A Novel Beamspace Channel Estimation Technique for Millimeter Wave Massive MIMO Systems

2019 3rd International Conference on Electrical, Computer & Telecommunication Engineering (ICECTE) ◽

10.1109/icecte48615.2019.9303527 ◽

2019 ◽

Author(s):

Prosenjit Paul ◽

Md Munjure Mowla

Keyword(s):

Channel Estimation ◽

Millimeter Wave ◽

Massive Mimo ◽

Mimo Systems ◽

Estimation Technique

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Channel Estimation for Millimeter Wave Massive MIMO Systems Using Separable Compressive Sensing

IEEE Access ◽

10.1109/access.2021.3069335 ◽

2021 ◽

Vol 9 ◽

pp. 49738-49749

Author(s):

Ting Jiang ◽

Maozhong Song ◽

Xuejian Zhao ◽

Xu Liu

Keyword(s):

Channel Estimation ◽

Compressive Sensing ◽

Millimeter Wave ◽

Massive Mimo ◽

Mimo Systems

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A Semi-Blind Channel Estimation Algorithm for One-bit Massive MIMO Systems

2018 IEEE 5G World Forum (5GWF) ◽

10.1109/5gwf.2018.8516943 ◽

2018 ◽

Cited By ~ 1

Author(s):

B. Srinivas ◽

Debarati Sen ◽

Saswat Chakrabarti

Keyword(s):

Channel Estimation ◽

Massive Mimo ◽

Mimo Systems ◽

Estimation Algorithm ◽

Blind Channel Estimation ◽

Blind Channel

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Propagation Path Loss Modeling and Outdoor Coverage Measurements Review in Millimeter Wave Bands for 5G Cellular Communications

International Journal of Electrical and Computer Engineering (IJECE) ◽

10.11591/ijece.v8i4.pp2254-2260 ◽

2018 ◽

Vol 8 (4) ◽

pp. 2254 ◽

Cited By ~ 1

Author(s):

Mohammed B. Majed ◽

Tharek A. Rahman ◽

Omar Abdul Aziz

Keyword(s):

Communication Networks ◽

Millimeter Wave ◽

Wide Spectrum ◽

Path Loss ◽

Separation Distance ◽

Propagation Path ◽

Delay Spread ◽

Propagation Time ◽

60 Ghz ◽

Rms Delay Spread

The global bandwidth inadequacy facing wireless carriers has motivated the exploration of the underutilized millimeter wave (mm-wave) frequency spectrum for future broadband cellular communication networks, and mmWave band is one of the promising candidates due to wide spectrum. This paper presents propagation path loss and outdoor coverage and link budget measurements for frequencies above 6 GHz (mm-wave bands) using directional horn antennas at the transmitter and omnidirectional antennas at the receiver. This work presents measurements showing the propagation time delay spread and path loss as a function of separation distance for different frequencies and antenna pointing angles for many types of real-world environments. The data presented here show that at 28 GHz, 38 GHz and 60 GHz, unobstructed Line of Site (LOS) channels obey free space propagation path loss while non-LOS (NLOS) channels have large multipath delay spreads and can utilize many different pointing angles to provide propagation links. At 60 GHz, there is more path loss and smaller delay spreads. Power delay profiles PDPs were measured at every individual pointing angle for each TX and RX location, and integrating each of the PDPs to obtain received power as a function of pointing angle. The result shows that the mean RMS delay spread varies between 7.2 ns and 74.4 ns for 60 GHz and 28 GHz respectively in NLOS scenario.

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Research on 5G Millimeter Wave Channel Estimation Algorithm

International Journal of Scientific Research in Science Engineering and Technology ◽

10.32628/ijsrset19651 ◽

2019 ◽

pp. 74-77

Author(s):

Xu Shuang

Keyword(s):

Channel Estimation ◽

Millimeter Wave ◽

Massive Mimo ◽

Large Scale ◽

Low Frequency ◽

Estimation Algorithm ◽

Simulation Research ◽

Wave Technology ◽

Wave Channel ◽

Mimo Technology

With the explosive growth in the number of communication users and the huge demand for data from users, Limited low-frequency resources have been far from being satisfied by users. The combination of Massive MIMO technology and millimeter-wave technology has brought new hope to users. In this paper, several basic algorithms are placed under the millimeter wave large-scale antenna channel for simulation research.

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