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

Sparse Channel Estimation for MIMO-OFDM Amplify-and-Forward Two-Way Relay Networks