Advanced Hybrid Information Processing. Second EAI International Conference, ADHIP 2018, Yiyang, China, October 5-6, 2018, Proceedings

Research Article

Channel Estimation for mmWave Massive MIMO via Phase Retrieval

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  • @INPROCEEDINGS{10.1007/978-3-030-19086-6_39,
        author={Zhuolei Xiao and Yunyi Li and Guan Gui},
        title={Channel Estimation for mmWave Massive MIMO via Phase Retrieval},
        proceedings={Advanced Hybrid Information Processing. Second EAI International Conference, ADHIP 2018, Yiyang, China, October 5-6, 2018, Proceedings},
        proceedings_a={ADHIP},
        year={2019},
        month={5},
        keywords={Channel estimation Received signal strength Sparse channel Phase retrieval},
        doi={10.1007/978-3-030-19086-6_39}
    }
    
  • Zhuolei Xiao
    Yunyi Li
    Guan Gui
    Year: 2019
    Channel Estimation for mmWave Massive MIMO via Phase Retrieval
    ADHIP
    Springer
    DOI: 10.1007/978-3-030-19086-6_39
Zhuolei Xiao,*, Yunyi Li1, Guan Gui1,*
  • 1: Nanjing University of Posts and Telecommunications
*Contact email: sky_south@163.com, guiguan@njupt.edu.cn

Abstract

The research on channel estimation technology is a core technology for mmWave massive MIMO in 5G wireless communications. This paper proposed a greedy iterative phase retrieval algorithm for channel estimation from received signal strength (RSS) feedback which is common in wireless communication systems and is used to compensate for temporal channels. We consider a Modified Gauss-Newton (MGN) algorithm to approximate the square term of the system model as a linear problem at each iteration and it is embedded in the 2-opt framework for iteration to get the optimal estimation. Our algorithm does not need to modify the system, but only need RSS feedback for channel estimation. The simulation results show that the algorithm performs better than the traditional conventional algorithm.