Background 5: Estimation Theory

This is a background video for the course Multiple Antenna Communications at Linköping University and KTH. It provides a summary of key results related to estimation theory, with focus on the Bayesian MMSE estimator. The estimation of a Gaussian distributed channel observed in Gaussian distributed noise is exemplified.

The slides are available here:

[alirezanavi]

Hello, Thank you for the lecture, it was so useful. I just had a question.
In this method, we need prior knowledge, the parameter beta, to be able to use MSE. In real-world scenarios, how is this information obtained?
thank you

[umerashraf]

Lectures on other types of estimators will be appreciated

[huuducdo]

Hello, thank you very much for your lectures. Can I have the prove of bayesian function of g given y (the one finally link to the gaussian distribution of g, at 9.50 of the video)? Thank you very much.

[getsamik]

How size of pilot bits are decided as to estimate we require sample size and depending on sample size, estimator's performance varies. Does it depends on frequency band.

[niravpatel]

sir here mmse estimation is carried out for Gaussian distributed variables. however, if we are interested for rician distributed variables mmse estimation then what will be change in to the derivation provided in to the video or where I will find it . kindly provide link or details of it.