  Extremely large-scale multiple-input multiple-output (XL-MIMO) is a promising
technique to enable versatile applications for future wireless
communications.To realize the huge potential performance gain, accurate channel
state information is a fundamental technical prerequisite. In conventional
massive MIMO, the channel is often modeled by the far-field planar-wavefront
with rich sparsity in the angular domain that facilitates the design of
low-complexity channel estimation. However, this sparsity is not conspicuous in
XL-MIMO systems due to the non-negligible near-field spherical-wavefront. To
address the inherent performance loss of the angular-domain channel estimation
schemes, we first propose the polar-domain multiple residual dense network
(P-MRDN) for XL-MIMO systems based on the polar-domain sparsity of the
near-field channel by improving the existing MRDN scheme. Furthermore, a
polar-domain multi-scale residual dense network (P-MSRDN) is designed to
improve the channel estimation accuracy. Finally, simulation results reveal the
superior performance of the proposed schemes compared with existing benchmark
schemes and the minimal influence of the channel sparsity on the proposed
schemes.
