  Accurate channel state information (CSI) is necessary for coherent detection
in amplify and forward (AF) broadband cooperative communication systems. Based
on the assumption of ordinary sparse channel, efficient sparse channel
estimation methods have been investigated in our previous works. However, when
the cooperative channel exhibits partial sparse structure rather than ordinary
sparsity, our previous method cannot take advantage of the prior information.
In this paper, we propose an improved channel estimation method with partial
sparse constraint on cooperative channel. At first, we formulate channel
estimation as a compressive sensing problem and utilize sparse decomposition
theory. Secondly, the cooperative channel is reconstructed by LASSO with
partial sparse constraint. Finally, numerical simulations are carried out to
confirm the superiority of proposed methods over ordinary sparse channel
estimation methods.
