Approximate Neumann Series or Exact Matrix Inversion for Massive MIMO?

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...

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Bibliographic Details
Main Authors: Gustafsson, Oscar, Bertilsson, Erik, Klasson, Johannes, Ingemarsson, Carl
Format: Conference Proceeding
Language:English
Subjects:
Clocks
complexity
Complexity theory
Computer architecture
Large-scale MIMO
Latency
Massive MIMO
Matrix inversion
MIMO
Neumann series
parallel processing
Pipeline processing
Symmetric matrices
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Summary: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.
ISSN:1063-6889
DOI:10.1109/ARITH.2017.11