I am newbie in compressive sensing (CS), I read about compressive sensing and its use for sparse vector estimation. As I understood CS can be used either in time or frequency domain. For me, The part I couldn't understand in my case is how to build the measurement matrix for my vector required to be estimated. (In my case the sparse vector $h$ needs to be estimated)
I have a vector $X$ where some values of it are known (let's say the values located at $1:4:end$), called pilots, that vector was convoluted with a sparse vector $h$, to have:
$y = X*h$
$*$ denotes the convolution operation.
My goal is to estimate the sparse vector $h$ based on the known values (pilots) in $X$. How to build the measurement matrix in that case?