Decoding Method Based on Complex ICA for a Multicell Massive MIMO Uplink System

被引:10
作者
Liu, Yangyi [1 ]
Wang, Haiquan [1 ]
Zhang, Wan [1 ]
Xu, Qian [1 ]
Shen, Lei [1 ]
机构
[1] Hangzhou Dianzi Univ, Sch Commun Engn, Hangzhou 310018, Zhejiang, Peoples R China
关键词
Independent component analysis (ICA); multicell massive multiple-input; multiple-output (MIMO) system; pilot contamination; pilot signals; principal component analysis (PCA); semi-blind decoding; CHANNEL ESTIMATION; DESIGN;
D O I
10.1109/LSP.2016.2545105
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Pilot signal reuse in neighboring cells causes the pilot contamination, and performance will be degraded significantly in a multicell, massive multiple-input, multiple-output (MIMO) uplink system. In this letter, a new decoding method is proposed to alleviate the degradation. In the proposed method, the principal component analysis (PCA) is used to reduce the dimension of the received signals from both intercell and intracell. Then, the complex independent component analysis (ICA) is implemented to estimate the channels, and the mean minimum square error (MMSE) decoder is employed to decode the transmitted signals. At last, few pilot signals are used to overcome the ambiguity caused by the complex ICA. In our method, orthogonality or asymptotic orthogonality of the channels is not required. Moreover, the path-loss and shadowing factors can be unknown. Simulation results show that the performance of our decoder is better than the MMSE channel estimation-based MMSE decoder. Moreover, error floor does not appear even when signal-to-noise ratio (SNR) is high, while it occurs if the MMSE decoder is used.
引用
收藏
页码:648 / 652
页数:5
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