  Amplify-and-forward two-way relay network (AFTWRN) was introduced to realize
high-data rate transmission over the wireless frequency-selective channel.
However, AFTWRC requires the knowledge of channel state information (CSI) not
only for coherent data detection but also for the selfdata removal. This is
partial accomplished by training sequence-based linear channel estimation.
However, conventional linear estimation techniques neglect anticipated sparsity
of multipath channel and thus lead to low spectral efficiency which is scarce
in the field of wireless communication. Unlike the previous methods, we propose
a sparse channel estimation method which can exploit the sparse structure and
hence provide significant improvements in MSE performance when compared with
traditional LS-based linear channel probing strategies in AF-TWRN. Simulation
results confirm the proposed methods.
