Compressed sensing-based near-field channel estimation method and apparatus for extra-large-scale massive multiple-input multiple-output (xl-mimo), device, and storage medium

A compressed sensing-based near-field channel estimation apparatus for XL-MIMO, comprising:

• a channel vector obtaining module and an estimate calculation module, wherein
• the channel vector obtaining module is configured to obtain a channel vector of a compressed sensing-based near-field channel on which estimation is to be performed;
• and
• the estimate calculation module is configured to input the channel vector into a channel estimation model constructed by a deep neural network, whereby the channel estimation model converts the channel vector into a polar-domain channel vector by a built-in sparse transformation matrix;
• compress the polar-domain channel vector into a signal vector by a built-in sensing matrix;
• add noise to the signal vector, and obtain a received signal vector;
• input the received signal vector into a built-in LAMP algorithm layer, whereby the LAMP algorithm layer performs an iterative calculation on the received signal vector by a built-in soft-thresholding function, and obtain an estimated polar-domain channel vector corresponding to the polar-domain channel vector, wherein the soft-thresholding function is calculated based on a built-in linear transformation parameter, nonlinear transformation parameter, and linear transformation matrix;
• and convert, by the built-in sparse transformation matrix, the estimated polar-domain channel vector into an estimate of the compressed sensing-based near-field channel on which estimation is to be performed.