  Accurate channel impulse response (CIR) is required for coherent detection
and it can also help improve communication quality of service in
next-generation wireless communication systems. One of the advanced systems is
multi-input multi-output orthogonal frequency-division multiplexing (MIMO-OFDM)
amplify and forward two-way relay networks (AF-TWRN). Linear channel estimation
methods, e.g., least square (LS), have been proposed to estimate the CIR.
However, these methods never take advantage of channel sparsity and then cause
performance loss. In this paper, we propose a sparse channel estimation method
to exploit the sparse structure information in the CIR at each end user. Sparse
channel estimation problem is formulated as compressed sensing (CS) using
sparse decomposition theory and the estimation process is implemented by LASSO
algorithm. Computer simulation results are given to confirm the superiority of
proposed method over the LS-based channel estimation method.
