Coefficient adjustment matrix inversion approach and architecture for massive MIMO systems

Coefficient adjustment matrix inversion approach and architecture for massive MIMO systems
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DOI:
10.1109/asicon.2015.7517048
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发表时间:
2015-11
期刊:
2015 IEEE 11th International Conference on ASIC (ASICON)
影响因子:
--
通讯作者:
X. Liang;Chuan Zhang;Shugong Xu;X. You
X. Liang;Chuan Zhang;Shugong Xu;X. You
中科院分区:
其他
文献类型:
--
作者:
X. Liang;Chuan Zhang;Shugong Xu;X. You

文献摘要

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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 × 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.