A fast and low-complexity matrix inversion scheme based on CSM method for massive MIMO systems.

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Bibliographic Details
Title:	A fast and low-complexity matrix inversion scheme based on CSM method for massive MIMO systems.
Authors:	Xu, Yue¹, Zou, Weixia¹, Du, Liutong²
Source:	EURASIP Journal on Wireless Communications & Networking. 10/18/2016, Vol. 2016 Issue 1, p1-6. 6p.
Subjects:	MIMO systems, Performance of MIMO systems, Sherman-Morrison-Woodbury formula, Wireless communications, Von Neumann algebras
Abstract:	Massive multiple-input-multiple-output (MIMO), also known as very-large MIMO systems, is an attracting technique in 5G and can provide higher rates and power efficiency than 4G. Linear-precoding schemes are able to achieve the near optimal performance, and thus are more attractive than non-linear precoding schemes. However, conventional linear precoding schemes in massive MIMO systems, such as regularized zero-forcing (RZF) precoding, have near-optimal performance but suffer from high computational complexity due to the required matrix inversion of large size. To solve this problem, we utilize the Cholesky-decomposition and Sherman-Morrison lemma and propose CSM (Cholesky and Sherman-Morrison strategy)-based precoding scheme to the matrix inversion by exploiting the asymptotically orthogonal channel property in massive MIMO systems. Results are evaluated numerically in terms of bit-error-rate (BER)and average sum rate. Comparing with the Neumann series approximation of inversing matrix, it is concluded that, with fewer operations, the performance of CSM-based precoding is better than conventional methods in massive MIMO configurations. [ABSTRACT FROM AUTHOR]
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Database:	Engineering Source

Description
Abstract:	Massive multiple-input-multiple-output (MIMO), also known as very-large MIMO systems, is an attracting technique in 5G and can provide higher rates and power efficiency than 4G. Linear-precoding schemes are able to achieve the near optimal performance, and thus are more attractive than non-linear precoding schemes. However, conventional linear precoding schemes in massive MIMO systems, such as regularized zero-forcing (RZF) precoding, have near-optimal performance but suffer from high computational complexity due to the required matrix inversion of large size. To solve this problem, we utilize the Cholesky-decomposition and Sherman-Morrison lemma and propose CSM (Cholesky and Sherman-Morrison strategy)-based precoding scheme to the matrix inversion by exploiting the asymptotically orthogonal channel property in massive MIMO systems. Results are evaluated numerically in terms of bit-error-rate (BER)and average sum rate. Comparing with the Neumann series approximation of inversing matrix, it is concluded that, with fewer operations, the performance of CSM-based precoding is better than conventional methods in massive MIMO configurations. [ABSTRACT FROM AUTHOR]
ISSN:	16871472
DOI:	10.1186/s13638-016-0749-3