Minshan Xiang’s research while affiliated with Beijing University of Posts and Telecommunications and other places

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Publications (2)


Model of polar antenna array of BS
Time‐domain channel of a UE to BS adjacent antennas
(a) NLOS case, (b) LOS case
Multi‐path energy accounts for the total energy ratio CDF
NMSE performance of different channel estimation schemes in NLOS case
NMSE performance of different channel estimation schemes in LOS case
Channel estimation for 3D MIMO system based on LOS/NLOS identification
  • Article
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April 2019

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69 Reads

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5 Citations

Minshan Xiang

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Yongyu Chang

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Channel estimation is one of the most important parts in three-dimensional multiple-input multiple-output (3D MIMO) systems. The characteristics of non-line-of-sight (NLOS) channel and line-of-sight (LOS) channel are different in 3D MIMO systems. If the same channel estimation scheme is used in LOS case as NLOS, the performance of estimation will be bad. In outdoor propagation environment, 3D MIMO channels between closely located antennas share the same delay support in temporal domain. With those prior knowledge, in this study, a new channel estimation scheme is proposed. The proposed scheme can be divided into two processes. First, it is needed to identify the received sounding reference signal whether is LOS or NLOS propagation. Then, different enhanced DFT-based channel estimation schemes are proposed separately according to the identification results. Simulation results verify the proposed algorithm outperforms traditional discrete Fourier transform (DFT)-based channel estimation. At signal-to-noise ratio of 20 dB, the proposed algorithm has 17.7 and 35.7% improvement in NLOS case and LOS case separately in terms of normalised mean squared error compared with traditional DFT-based channel estimation scheme, and is achieved with additional liner complexity.

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Citations (1)


... There are many excellent research works [3][4][5][6][7] and reviews [8][9][10] in the literature dealing with the channel estimation. In recent years, the research on channel estimation mainly focuses on the following aspects: channel estimation based on deep learning, 11,12 channel estimation based on iteration, [13][14][15] and channel estimation based on compressive sensing (CS). ...

Reference:

The research on channel estimation and signal‐noise ratio estimation based on minimum error entropy kalman filter for single carrier frequency domain equalization system
Channel estimation for 3D MIMO system based on LOS/NLOS identification