Abstract
Multiple-Input Multiple-Output (MIMO) is one of the key technology components in the fifth generation communication (5G). Inevitably, the growing antenna number in a limited space makes mutual coupling (MC) effect severely influence the system performance of wireless communication. Therefore, accurate MC modeling is of great significance to eliminate MC effects. To this end, we propose a new MC modeling approach based on deep learning to model MC effect in massive MIMO system. For the sake of realizing the processing of complex data with deep neural network (DNN), we divide the complex data into real and imaginary parts, and deduce the expression of mean square error (MSE) of complex data. Then a baseband decoupling algorithm with hybrid beamforming structure has been proposed to eliminate the MC effect. Simulation results show that, in terms of MSE and bit error rate (BER), the proposed deep learning based MC modeling method has an impressive modeling accuracy and perfect performance of decoupling.
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