Disclosed in the present invention is a compressed sensing-based large scale MIMO channel feedback reconstruction algorithm, comprising the following steps: S1. a system model setup step: installing multiple antennas at a base station for simultaneously serving multiple users, each user being received by means of a single antenna, the antennas at the base station end being uniformly and linearly arranged, and a receiving end obtaining a channel matrix by means of channel estimation; 2. a channel state information compression step: vectorizing the channel matrix to obtain a vector, compressing the vector by means of an observation matrix to obtain an observation vector, and sending the observation vector y to the base station end by means of a feedback link; S3. a channel state information reconstruction step: after the base station end receives the observation vector, performing numerical initialization and cyclic iteration, and finally obtaining a reconstruction signal. According to the present invention, a generalized orthogonal matching pursuit algorithm is used as a channel feedback reconstruction algorithm, the number of iterations is reduced, and not only the reconstruction precision of the channel state information is effectively improved, but also the reconstruction time is shortened.
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