Computer Engineering and Applications ›› 2020, Vol. 56 ›› Issue (5): 118-124.DOI: 10.3778/j.issn.1002-8331.1901-0204

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Weighted Orthogonal Matching Pursuit Channel Estimation Algorithm for Massive MIMO Systems

SUN Zeyu, LV Zhiguo   

  1. 1.School of Computer and Information Engineering, Luoyang Institute of Science and Technology, Luoyang, Henan 471023, China
    2.Luoyang Key Laboratory of Intelligent Agriculture Husbandry Sensor Networks, Luoyang, Henan 471023, China
    3.State Key Laboratory of Integrated Service Networks, Xidian University, Xi’an 710071, China
  • Online:2020-03-01 Published:2020-03-06



  1. 1.洛阳理工学院 计算机与信息工程学院,河南 洛阳 471023
    2.洛阳智能农牧业传感网重点实验室,河南 洛阳 471023
    3.西安电子科技大学 综合业务网理论及关键技术国家重点实验室,西安 710071


Massive Multiple Input Multiple Output(MIMO) systems have massive antennas at base station. The high dimension of the channel makes it difficult for mobile users to accurately estimate downlink channel in real time. To address this issue, a weighted Orthogonal Matching Pursuit(OMP) algorithm is proposed in this paper. Firstly, the estimated signal calculated by the algorithm in each iteration is divided into two parts, the signal estimated from current residual signal and the signal estimated from previous residual signal. Secondly, these two parts of the signal are set with different weights to improve the estimation accuracy under low Signal Noise Ratio(SNR). Moreover, by adjusting the weight values with iterations, the estimation accuracy of the channel under both low and high SNR can be improved. The simulation results show that the proposed algorithm can obtain higher estimation accuracy than the standard OMP algorithm under different signal-to-noise ratios.

Key words: massive Multiple Input Multiple Output(MIMO), channel estimation, sparse reconstruction, compressed sensing, orthogonal matching pursuit



关键词: 大规模多输入多输出(MIMO), 信道估计, 稀疏重建, 压缩感知, 正交匹配追踪