This paper proposes a superimposed training strategy to estimate the individual frequency and channel parameters in an amplify-and-forward (AF) two-way relay network (TWRN). Two efficient suboptimal estimation algorithms and an iterative process to further improve the performance are proposed. The estimation Cramér-Rao Bound (CRB) on the proposed estimation strategy is also derived. The simulations confirm that the iterative estimation process converges rapidly and that the resultant estimation mean square error (MSE) approaches the CRB, especially for the case when the carrier frequency offset between the two source terminals is small.
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