Deep Learning Based MIMO Transmission with Precoding and Radio Transformer Networks

Wenqi Cui, Anming Dong, Yi Cao, Chuanting Zhang, Jiguo Yu, Sufang Li

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we study MIMO transmission schemes based on deep learning (DL). We propose a novel DL-based MIMO communication structure by combing a beamforming network at the transmitter side and a radio transformer network (RTN) at the receiver side. Compared with the classical DL-based MIMO communication systems, the interference is potentially mitigated by a precoding network and a RTN network, which is thus beneficial to improve the performance of signal detection. Simulation results show that the proposed scheme outperforms the classical MIMO transmission schemes in terms of bit error rate (BER).
Original languageEnglish (US)
Title of host publicationProcedia Computer Science
PublisherElsevier BV
Pages396-401
Number of pages6
DOIs
StatePublished - Jun 12 2021

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