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Compressed Sensing (CS) has recently emerged as a powerful signal acquisition paradigm. CS enables the recovery of high-dimensional sparse signals from much fewer samples than usually required. Further, quite a few recent channel measurement experiments show that many wireless channels also tend to exhibit sparsity. In this case, CS theory can be applicable to sparse channel estimation and its effectiveness has been validated in Point-To-Point (P2P) communication. In this paper, the authors study sparse channel estimation for Two-Way Relay Networks (TWRN). Unlike P2P systems, applying CS theory to sparse channel estimation in TWRN is much more challenging.
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