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
Schlagworte:
Approximation
Asymptotic properties
Channels
Communications Engineering
Engineering
Information Systems Applications (incl.Internet)
Inversions
Mathematical analysis
Mathematical models
MIMO (control systems)
Networks
Radar and Sonar Networks
Signal,Image and Speech Processing
Wireless communication
Cholesky-decomposition
CSM-based precoding
Sherman-Morrison lemma
Neumann series
Massive MIMO
RZF
ISSN:1687-1499, 1687-1472, 1687-1499
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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.
AbstractList 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.
ArticleNumber 251
Author Du, Liutong
Zou, Weixia
Xu, Yue
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  givenname: Yue
  orcidid: 0000-0003-4946-049X
  surname: Xu
  fullname: Xu, Yue
  email: yuexu24@163.com
  organization: KeyLab of Universal Wireless Communications, MOE, Beijing University of Posts and Telecommunications
– sequence: 2
  givenname: Weixia
  surname: Zou
  fullname: Zou, Weixia
  organization: KeyLab of Universal Wireless Communications, MOE, Beijing University of Posts and Telecommunications
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  givenname: Liutong
  surname: Du
  fullname: Du, Liutong
  organization: State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications
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crossref_primary_10_1049_joe_2018_5015
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10.1109/JSTSP.2014.2317671
10.1109/TIT.1983.1056659
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10.1109/TSP.2013.2282920
10.1109/TIT.2008.2006426
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Issue 1
Keywords Cholesky-decomposition
CSM-based precoding
Sherman-Morrison lemma
Neumann series
Massive MIMO
RZF
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PublicationTitle EURASIP journal on wireless communications and networking
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Springer Nature B.V
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Snippet 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...
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SubjectTerms Approximation
Asymptotic properties
Channels
Communications Engineering
Engineering
Information Systems Applications (incl.Internet)
Inversions
Mathematical analysis
Mathematical models
MIMO (control systems)
Networks
Radar and Sonar Networks
Signal,Image and Speech Processing
Wireless communication
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Title A fast and low-complexity matrix inversion scheme based on CSM method for massive MIMO systems
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Volume 2016
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