scholarly journals Sparse-Based Millimeter Wave Channel Estimation With Mutual Coupling Effect

Electronics ◽  
2019 ◽  
Vol 8 (3) ◽  
pp. 358 ◽  
Author(s):  
Zhenxin Cao ◽  
Haiyang Geng ◽  
Zhimin Chen ◽  
Peng Chen
Keyword(s):  
Channel Estimation ◽  
Millimeter Wave ◽  
Communication System ◽  
Mutual Coupling ◽  
Coupling Effect ◽  
Sparse Signals ◽  
Communication Performance ◽  
Estimation Performance ◽  
Wave Channel ◽  
Direction Of Departure

The imperfection of antenna array degrades the communication performance in the millimeter wave (mmWave) communication system. In this paper, the problem of channel estimation for the mmWave communication system is investigated, and the unknown mutual coupling (MC) effect between antennas is considered. By exploiting the channel sparsity in the spatial domain with mmWave frequency bands, the problem of channel estimation is converted into that of sparse reconstruction. The MC effect is described by a symmetric Toeplitz matrix, and the sparse-based mmWave system model with MC coefficients is formulated. Then, a two-stage method is proposed by estimating the sparse signals and MC coefficients iteratively. Simulation results show that the proposed method can significantly improve the channel estimation performance in the scenario with unknown MC effect and the estimation performance for both direction of arrival (DOA) and direction of departure (DoD) can be improved by about 8 dB by reducing the MC effect about 4 dB.

scholarly journals Sparse DOD/DOA Estimation in a Bistatic MIMO Radar With Mutual Coupling Effect

Electronics ◽  
2018 ◽  
Vol 7 (11) ◽  
pp. 341 ◽  
Author(s):  
Peng Chen ◽  
Zhenxin Cao ◽  
Zhimin Chen ◽  
Chunhua Yu
Keyword(s):  
Mutual Coupling ◽  
Coupling Effect ◽  
Doa Estimation ◽  
Mimo Radar ◽  
Joint Estimation ◽  
Reconstruction Method ◽  
Estimation Model ◽  
Unknown Parameters ◽  
Estimation Performance ◽  
Direction Of Departure

The unknown mutual coupling effect between antennas significantly degrades the target localization performance in the bistatic multiple-input multiple-output (MIMO) radar. In this paper, the joint estimation problem for the direction of departure (DOD) and direction of arrival (DOA) is addressed. By exploiting the target sparsity in the spatial domain and formulating a dictionary matrix with discretizing the DOD/DOA into grids, compressed sensing (CS)-based system model is given. However, in the practical MIMO radar systems, the target cannot be precisely on the grids, and the unknown mutual coupling effect degrades the estimation performance. Therefore, a novel CS-based DOD/DOA estimation model with both the off-grid and mutual coupling effect is proposed, and a novel sparse reconstruction method is proposed to estimate DOD/DOA with updating both the off-grid and mutual coupling parameters iteratively. Moreover, to describe the estimation performance, the corresponding Cramér–Rao lower bounds (CRLBs) with all the unknown parameters are theoretically derived. Simulation results show that the proposed method can improve the DOD/DOA estimation in the scenario with unknown mutual coupling effect, and outperform state-of-the-art methods.

scholarly journals Research on 5G Millimeter Wave Channel Estimation Algorithm

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.

scholarly journals Tensor-Based Angle Estimation Approach for Strictly Noncircular Sources with Unknown Mutual Coupling in Bistatic MIMO Radar

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2788 ◽  
Author(s):  
Yuehao Guo ◽  
Xianpeng Wang ◽  
Wensi Wang ◽  
Mengxing Huang ◽  
Chong Shen ◽  
...  
Keyword(s):  
Mutual Coupling ◽  
Multiple Input Multiple Output ◽  
Estimation Method ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Mimo Radar ◽  
Angle Estimation ◽  
Estimation Performance ◽  
Direction Of Departure ◽  
Value Decomposition

In the paper, the estimation of joint direction-of-departure (DOD) and direction-of-arrival (DOA) for strictly noncircular targets in multiple-input multiple-output (MIMO) radar with unknown mutual coupling is considered, and a tensor-based angle estimation method is proposed. In the proposed method, making use of the banded symmetric Toeplitz structure of the mutual coupling matrix, the influence of the unknown mutual coupling is removed in the tensor domain. Then, a special enhancement tensor is formulated to capture both the noncircularity and inherent multidimensional structure of strictly noncircular signals. After that, the higher-order singular value decomposition (HOSVD) technology is applied for estimating the tensor-based signal subspace. Finally, the direction-of-departure (DOD) and direction-of-arrival (DOA) estimation is obtained by utilizing the rotational invariance technique. Due to the use of both noncircularity and multidimensional structure of the detected signal, the algorithm in this paper has better angle estimation performance than other subspace-based algorithms. The experiment results verify that the method proposed has better angle estimation performance.

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