Accurate channel impulse response (CIR) is required for coherent detection and it also helps to improve the quality of service in next-generation wireless communication systems. Linear channel estimation methods, e.g., least square (LS), have been proposed to estimate the CIR. However, these methods never take advantage of the channel sparsity and they also cause performance loss. In this paper, we propose a sparse channel estimation method for multi-input multi-output orthogonal frequency-division multiplexing (MIMO-OFDM) amplify and forward two-way relay networks (AF-TWRN), to exploit the sparse structure information in the CIR for each 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 the proposed method over the LS-based channel estimation.