Low-complexity sparse channel estimation for massive MIMO systems

Due to the high computational complexity of massive MIMO system,a low-complexity sparse channel estimation algorithm was proposed utilizing the inherent sparsity of the wireless communication channel to improve the estimation performance.The proposed algorithm separated channel tap from noise space...

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Bibliographic Details
Main Authors: Xin FANG, Yunju LIU, Haiyan CAO, Peng PAN
Format: Article
Language:zho
Published: Beijing Xintong Media Co., Ltd 2016-05-01
Series:Dianxin kexue
Subjects:
Online Access:http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2016149/
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Summary:Due to the high computational complexity of massive MIMO system,a low-complexity sparse channel estimation algorithm was proposed utilizing the inherent sparsity of the wireless communication channel to improve the estimation performance.The proposed algorithm separated channel tap from noise space based on the traditional discrete Fourier transform by adopting integral separation algorithm.This channel estimation algorithm need only calculate the channel tap,thus markedly reducing complexity of the algorithm.Numerical simulations show that proposed algorithm can approach to the performance of the minimum mean-square error estimator while maintaining lower complexity.
ISSN:1000-0801