Residual neural network based joint transmit-receive antenna selection in MIMO system

In large-scale MIMO system, as the number of antennas increases, the huge computational complexity makes traditional antenna selection algorithms impossible to effectively apply. This paper propose a joint transmitreceive antenna selection model based on ResNet. We utilize the optimal antenna selection algorithm to create labels for all channel matrices, which based on maximizing channel capacity criterion. Then using large-scale channel data to train a powerful residual neural network classifier. Consequently the trained model can classify the corresponding label for each channel matrix in the test set and select the optimal antenna subset. Experimental results show that the method can effectively decrease the number of antenna selection and its communication performance outperforms compared methods