基于压缩感知的大规模MIMO信道估计与反馈

doi:10.11959/j.issn.1000-0801.2018288

Abstract

Abstract:

Focused on the issue that the problem of low precision of channel estimation and complex feedback scheme in massive MIMO system,a compression sampling matching pursuit (BCC-CoSAMP) algorithm based on coefficient correlation was proposed in the differential channel estimation and feedback scheme.In this algorithm,the inner product of the relationship between two vectors in the CoSAMP algorithm was replaced by the vector relation based on the correlation coefficient,so the atoms with strong correlation of the original signal were quickly selected to improve the accuracy of channel estimation.The simulation results show that the proposed BCC-CoSAMP algorithm has an improved channel estimation accuracy compared with the CoSAMP algorithm and an average increase of the total system rate of 1.25 bit/(s.Hz) at low signal to noise ratio (SNR).

Key words: massive MIMO, compressive sampling matching pursuit, channel estimation, feedback overhead

CLC Number:

TN929.5

Pan MAO,Xiaoguang HUANG,Wei WANG,Jian SONG. Massive MIMO channel estimation and feedback based on compressed sensing[J]. Telecommunications Science, 2018, 34(12): 46-52.

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References 15

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参数	取值	说明
μ	0.1	分布概率
ρ₀₁	0.16	转移概率
f_d/Hz	10	最大多普勒频率
τ/ms	0.5	每个时隙持续时间
SNR/dB	0~20	信噪比
η	0.4~0.7	导频的平均开销
R	3	时隙长度
2σ_w	1	方差

Massive MIMO channel estimation and feedback based on compressed sensing

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