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When the proposed schemes are applied to periodic problems, only periodic bi-diagonal matrix inversions or periodic block-bi-diagonal matrix inversions are required.
However, extra costs are introduced, as matrix inversions are required when an MMSE filter is deployed.
The RX detector is naturally a computationally inefficient task since matrix inversions are required, in our analysis.
Such matrix inversions are required frequently due to changes in user status, or variations in crosstalk characteristics [14].
In order to compare the SIC scheme with the TG and MA schemes, the number of energy calculation iterations and also the number of matrix inversions are taken as the measurement parameter to examine and indicate the computational complexity of each scheme.
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Next, a class of implicit factorized schemes, which require scalar matrix inversions, is presented.
The number of matrix inversions is examined for the equal energy and iterative energy loading cases.
In this paper, VLSI array architectures for matrix inversion are studied.
In the present paper alternative techniques for regularizing the matrix inversion are considered.
Some interesting results for matrix inversion are derived and used to reduce the complexity of the Wiener filter expression.
Two methods of matrix inversion are implemented, namely Gauss-Jordan and Cholesky decomposition.
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