Title :
Biased MMSE soft-output detection based on Jacobi method in massive MIMO
Author :
Jiangyun Zhou ; Yu Ye ; Jianhao Hu
Author_Institution :
Nat. key Lab. of Commun., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
Abstract :
Massive (or large-scale) multi-input multi-output (MIMO) is a promising means to improve the energy efficiency, spectral efficiency and throughput. However, the complexity of the detection increases exponentially with the scale of MIMO system. In this paper, we propose a biased minimum mean-square error (MMSE) detection based on the Jacobi iterative method (JIM) to reduce the complexity of the massive MIMO detector. The proposed biased MMSE detection can provide the post-equalized signal-to-interference-and-noise-ratio (SINR) without iterative processing. Besides, if the Gray-mapping is used, the computational complexity of the bit-wise LLR will be reduced significantly. The simulation shows that the proposed detection method can achieve a better performance/complexity trade-offs than the existing detection methods.
Keywords :
MIMO communication; iterative methods; least mean squares methods; signal detection; Gray mapping; Jacobi iterative method; Jacobi method; biased MMSE soft-output detection; biased minimum mean square error detection; bitwise LLR; energy efficiency; massive MIMO; multiple input multiple output system; post equalized signal; signal-to-interference-ratio; signal-to-noise-ratio; spectral efficiency; Complexity theory; Equations; Iterative methods; Jacobian matrices; MIMO; Signal to noise ratio; Vectors; Jacobi iterative method; biased MMSE; massive MIMO; soft-output detection;
Conference_Titel :
Communication Problem-Solving (ICCP), 2014 IEEE International Conference on
Print_ISBN :
978-1-4799-4246-6
DOI :
10.1109/ICCPS.2014.7062317
