Telecommunications Science ›› 2016, Vol. 32 ›› Issue (5): 89-95.doi: 10.11959/j.issn.1000-0801.2016149

• research and development • Previous Articles     Next Articles

Low-complexity sparse channel estimation for massive MIMO systems

Xin FANG,Yunju LIU,Haiyan CAO,Peng PAN   

  1. School of Communication Engineering,Hangzhou Dianzi University,Hangzhou 310018,China
  • Online:2017-02-22 Published:2017-02-22
  • Supported by:
    The National Natural Science Foundation of China for Youths;The Natural Science Foundation of Zhejiang Province;Solid State Storage and Data Security Key Technology of Zhejiang Province

Abstract:

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.

Key words: massive MIMO, channel estimation, sparsity, algorithm complexity

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