The invention discloses a
millimeter wave
MIMO user incremental cooperative beam
selection method based on wide learning, which comprises the following steps that: aiming at the downlink beam selection problem of a multipoint cooperative
millimeter wave large-scale
MIMO scene, each user collects downlink
wide beam response and transmission
narrow beam response, trains a local wide
learning network, and transmits the downlink
wide beam response to the local wide
learning network; and beam selection is carried out based on the predicted
narrow beam response. Furthermore, the training problem of the local network of each user is modeled into a distributed
optimization problem with consistency constraint, and effective sharing of training data can be realized by utilizing D2D communication between adjacent users. Furthermore, an incremental updating mode of the local network of the user in the cooperation mode is designed, so that the training complexity of the network can be effectively reduced. According to the method, the capability of mining the relationship between the multi-base-
station wide beam response and the transmission
narrow beam response under the
small sample condition of distributed wide learning is fully utilized, and low-complexity and low-overhead beam selection of the fast time-varying scene multipoint cooperation
millimeter wave large-scale
system can be realized.