Channel Estimation Based Compressive Sensing in Millimeter Wave MIMO systems

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.

Download Full-text

Channel Estimation for Millimeter Wave MIMO Systems in the Presence of CFO Uncertainties

2018 IEEE International Conference on Communications (ICC) ◽

10.1109/icc.2018.8422342 ◽

2018 ◽

Cited By ~ 1

Author(s):

Javier Rodriguez-Fernandez ◽

Nuria Gonzalez-Prelcic ◽

Robert W. Heath

Keyword(s):

Channel Estimation ◽

Millimeter Wave ◽

Mimo Systems

Download Full-text

Doubly Selective Channel Estimation Algorithms for Millimeter Wave Hybrid MIMO Systems

IEEE Transactions on Vehicular Technology ◽

10.1109/tvt.2021.3120298 ◽

2021 ◽

pp. 1-1

Author(s):

Ali Mohebbi ◽

Hamed Abdzadeh-Ziabari ◽

Wei-Ping Zhu ◽

M. Omair Ahmad

Keyword(s):

Channel Estimation ◽

Millimeter Wave ◽

Mimo Systems ◽

Doubly Selective Channel ◽

Estimation Algorithms ◽

Selective Channel

Download Full-text

Low-Complexity Downlink Channel Estimation for Millimeter-Wave FDD Massive MIMO Systems

IEEE Wireless Communications Letters ◽

10.1109/lwc.2019.2907955 ◽

2019 ◽

Vol 8 (4) ◽

pp. 1103-1107 ◽

Cited By ~ 2

Author(s):

Xianda Wu ◽

Guanghua Yang ◽

Fen Hou ◽

Shaodan Ma

Keyword(s):

Channel Estimation ◽

Millimeter Wave ◽

Massive Mimo ◽

Mimo Systems ◽

Low Complexity

Download Full-text

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

Entropy ◽

10.3390/e22101121 ◽

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.

Download Full-text