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Approximate Neumann Series or Exact Matrix Inversion for Massive MIMO? (Invited Paper)
Linköping University, Department of Electrical Engineering, Computer Engineering.ORCID iD: 0000-0003-3470-3911
Linköping University, Department of Electrical Engineering, Computer Engineering.
Linköping University, Department of Electrical Engineering, Computer Engineering.
Linköping University, Department of Electrical Engineering, Computer Engineering.
2017 (English)Conference paper, (Refereed)
Abstract [en]

Approximate matrix inversion based on Neumann series has seen a recent increased interest motivated by massive MIMO systems. There, the matrices are in many cases diagonally dominant, and, hence, a reasonable approximation can be obtained within a few iterations of a Neumann series. In this work, we clarify that the complexity of exact methods are about the same as when three terms are used for the Neumann series, so in this case, the complexity is not lower as often claimed. The second common argument for Neumann series approximation, higher parallelism, is indeed correct. However, in most current practical use cases, such a high degree of parallelism is not required to obtain a low latency realization. Hence, we conclude that a careful evaluation, based on accuracy and latency requirements must be performed and that exact matrix inversion is in fact viable in many more cases than the current literature claims.

Place, publisher, year, edition, pages
2017.
Keyword [en]
matrix inversion, complexity, parallel processing, massive MIMO
National Category
Computer Systems Signal Processing Communication Systems
Identifiers
URN: urn:nbn:se:liu:diva-139337OAI: oai:DiVA.org:liu-139337DiVA: diva2:1121300
Conference
IEEE Symposium on Computer Arithmetic
Available from: 2017-07-10 Created: 2017-07-10 Last updated: 2017-07-10

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