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Deep Learning-Based Rate-Splitting Multiple Access for Massive MIMO-OFDM Systems With Imperfect CSIT
ID：14 View Protection：PUBLIC Updated Time：2022-10-11 16:24:16 Hits：624 Oral Presentation

Start Time：2022-10-19 11:15（Asia/Shanghai）

Duration：15min

Session：SS Special Session » SS2SS2: Rate-Splitting Multiple Access for 6G

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Abstract
Due to the high dimensionality of the channel state information (CSI) in massive  multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems, acquiring accurate CSI at the transmitter (CSIT) with limited feedback overhead is difficult, severely degrading the performance of conventional SDMA beamforming techniques. To this end, this paper proposes a deep learning (DL)-based end-to-end (E2E) rate-splitting multiple access (RSMA) beamforming scheme for massive MIMO-OFDM systems, including an analog beamforming network (ABN) and a model-driven RSMA digital beamforming network (RDBN). We adopt an E2E training approach to jointly train the proposed ABN and MRBN to obtain better beamforming performance. Numerical results show that the proposed DL-based E2E RSMA beamforming scheme significantly improves the system capacity and outperforms the state-of-the-art schemes.
Keywords
rate-splitting multiple access (RSMA), deep learning, Transformer, hybrid beamforming
Speaker
Gao Zhen
Beijing Institute of Technology

Zhen Gao received the B.S. degree in information engineering from the Beijing Institute of Technology, Beijing, China, in 2011, and the Ph.D. degree in communication and signal processing with the Tsinghua National Laboratory for Information Science and Technology, Department of Electronic Engineering, Tsinghua University, China, in 2016.  He is currently an Assistant Professor with Beijing Institute of Technology. His research interests are in wireless communications, with a focus on multi-carrier modulations, multiple antenna systems, and sparse signal processing.
Dr. Gao was the recipient of IEEE Broadcast Technology Society 2016 Scott Helt Memorial Award (best paper), the recipient of Exemplary Reviewer of IEEE Communications Letters in 2016, and the recipient of IET Electronics Letters Premium Award (Best Paper) 2016, the recipient of Young Elite Scientists Sponsorship Program (2018-2021) by China Association for Science and Technology.

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Important Date

  • Conference Date

    Oct 19

    2022

    to

    Oct 22

    2022

Sponsored By
Zhejiang University
Organized By
Zhejiang University
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