2
$\begingroup$

SVD is a method to cancel the interference in MIMO system,we often do the SVD of channel as below

\begin{align} \mathbf{H} &= \mathbf{U} \ \Sigma \ \mathbf{V}^{T} \\ % \end{align}

So $ \mathbf{U}$ means the beamforming direction of receiver? and $\mathbf{V}$ means the beamforming direction of transmitter? and the singular value in the diagonal of $\Sigma$ means the gain of channel ?Why can we use this to decrease or cancel the noise ?

Improve this question
$\endgroup$
1
  • $\begingroup$ How do you define beamforming "direction"? I mean beamforming itself is the whole process from preprocessing $V$ to post processing $U$, and this is the only thing matters. For other questions, you can follow the answer of Peter K. $\endgroup$
    – AlexTP
    Commented Sep 19, 2019 at 11:14

1 Answer 1

Reset to default
2
$\begingroup$

Singular value decomposition (SVD) is a method of decomposing a matrix into two unitary matrices and a non-negative definite matrix of singular values.

In the context of MIMO communications, the $\mathbf{H}$ matrix defines the channel; it doesn't specify anything directly about the transmitter or the receiver.

This paper has the following diagram which shows one interpretation of the $\mathbf{U}$ and $\mathbf{V}$ matrices. The SVD allows the channel to be decomposed into several parallel paths, with no crosstalk between them.

Channel decomposition via SVD.

Improve this answer
$\endgroup$

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge you have read our privacy policy.

Not the answer you're looking for? Browse other questions tagged or ask your own question.