@inproceedings{06bb7d38023844c3ae3e9d50b908b964,
title = "Coefficient adjustment matrix inversion approach and architecture for massive MIMO systems",
abstract = "Thanks to hundreds of antennas, spectral efficiency of massive multiple-input multiple-output (MIMO) systems has drastically increased. However, the resulting huge dimension of matrices involved in massive MIMO MMSE detection causes prohibitive complexity. Although large scale matrix inversion with Neumann approximation achieves good tradeoff between complexity and accuracy for i.i.d. massive MIMO channel, its convergency speed degrades seriously for correlated massive MIMO channel. To this end, in this paper the matrix inversion approach based on coefficient adjustment (CA), which is more adaptable to correlated channel with higher throughput, is proposed. The corresponding hardware architecture is also given. FPGA results have shown that for 4 χ 32 MIMO system, the proposed architecture can achieve 69.4% higher frequency with only 49.1% hardware cost compared to Cholesky decomposition method. CA approach can also achieve 37.9% higher throughput than Neumann scheme for correlated channel on average.",
keywords = "coefficient adjustment, high throughput, low complexity, Matrix inversion, Neumann series",
author = "Xiao Liang and Chuan Zhang and Shugong Xu and Xiaohu You",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 11th IEEE International Conference on Advanced Semiconductor Integrated Circuits (ASIC), ASICON 2015 ; Conference date: 03-11-2015 Through 06-11-2015",
year = "2016",
month = jul,
day = "21",
doi = "10.1109/ASICON.2015.7517048",
language = "English",
series = "Proceedings - 2015 IEEE 11th International Conference on ASIC, ASICON 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
editor = "Junyan Ren and Ting-Ao Tang and Fan Ye and Huihua Yu",
booktitle = "Proceedings - 2015 IEEE 11th International Conference on ASIC, ASICON 2015",
}