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Principles of Linear MIMO Receivers

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Introduction to Digital Communications

Part of the book series: Signals and Communication Technology ((SCT))

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Abstract

As depicted in the block diagram of Fig. 18.1, we consider a MIMO system with frequency flat and in general time-varying channel with channel matrix \(\varvec{\mathrm {H}}(k)\,\epsilon \,\mathbb {C}^{N\mathrm {x}M}\), input signal vector \(\varvec{\mathrm {s}}(k)\,\epsilon \,\mathbb {C}^{M\mathrm {x}1}\), noise vector \(\varvec{\mathrm {n}}(k)\,\epsilon \,\mathbb {C}^{N\mathrm {x}1}\), and receive vector \(\varvec{\mathrm {r}}(k)\,\epsilon \,\mathbb {C}^{N\mathrm {x}1}\). At the receiver, a linear filter described by a matrix \(\varvec{\mathrm {W}}(k)\,\epsilon \,\mathbb {C}^{M\mathrm {x}N}\) is employed to obtain at its output a good replica \(\varvec{\mathrm {y}}(k)\) of the transmit signal vector \(\mathrm {\varvec{s}}(k)\). We assume that a channel estimator not shown in Fig. 18.1 has provided perfect channel state information so that the instantaneous channel matrix \(\mathbf {H}(k)\) is known for every discrete-time instant k at the receiver.

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Notes

  1. 1.

    Note \(\left( \alpha \mathbf {A}\right) ^{-1}=\frac{1}{\alpha }\mathbf {A}^{-1}\,;\,\alpha \ne 0\)

References

  1. E.H. Moore, On the reciprocal of the general algebraic matrix. Bull. Am. Math. Soc. 26 (1920)

    Google Scholar 

  2. R. Penrose, A generalized inverse for matrices. Proc. Camb. Philos. Soc. 51 (1955)

    Article  Google Scholar 

  3. A. Albert, Regression and the Moore-Penrose Pseudoinverse, vol. 94 (Elsevier, Academic Press, Amsterdam, 1972)

    Google Scholar 

  4. K.B. Petersen, M.S. Pedersen, The Matrix Cookbook (Technical University of Denmark, 2012), h. open source https://archive.org/details/imm3274

  5. A. Ben-Israel, T.N.E. Greville, Generalized Inverses (Springer, Berlin, 2003)

    Google Scholar 

  6. A. Hjorungnes, Complex-valued Matrix Derivatives with Applications in Signal Processing and Communications (Cambridge University Press, Cambridge, 2011)

    Google Scholar 

  7. R.A. Horn, C.R. Johnson, Matrix Analysis (Cambridge University Press, Cambridge, 2013)

    Google Scholar 

  8. B.B. Chaoudhry, Diversity combining, webdemo, Technical report. Institute of Telecommunications, University of Stuttgart, Germany (2018), http://webdemo.inue.uni-stuttgart.de

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Correspondence to Joachim Speidel .

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Speidel, J. (2019). Principles of Linear MIMO Receivers . In: Introduction to Digital Communications. Signals and Communication Technology. Springer, Cham. https://doi.org/10.1007/978-3-030-00548-1_18

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  • DOI: https://doi.org/10.1007/978-3-030-00548-1_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-00547-4

  • Online ISBN: 978-3-030-00548-1

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