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

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 pr...

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Veröffentlicht in:EURASIP journal on wireless communications and networking Jg. 2016; H. 1; S. 1 - 6
Hauptverfasser: Xu, Yue, Zou, Weixia, Du, Liutong
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Cham Springer International Publishing 19.10.2016
Springer Nature B.V
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ISSN:1687-1499, 1687-1472, 1687-1499
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Zusammenfassung: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.
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ISSN:1687-1499
1687-1472
1687-1499
DOI:10.1186/s13638-016-0749-3