Transformer-Empowered 6G Intelligent Networks: From Massive MIMO Processing to Semantic Communication

نویسندگان

چکیده

It is anticipated that 6G wireless networks will accelerate the convergence of physical and cyber worlds enable a paradigm-shift in way we deploy exploit communication networks. Machine learning, particular deep learning (DL), expected to be one key technological enablers by offering new paradigm for design optimization with high level intelligence. In this article, introduce an emerging DL architecture, known as transformer, discuss its potential impact on network design. We first differences between transformer classical architectures, emphasize transformer's self-attention mechanism strong representation capabilities, which make it particularly appealing tackling various challenges Specifically, propose transformer-based solutions massive multiple-input multiple-output (MIMO) semantic problems, show their superiority compared other architectures. Finally, open issues transformerbased solutions, identify future research directions deployment intelligent

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ژورنال

عنوان ژورنال: IEEE Wireless Communications

سال: 2022

ISSN: ['1558-0687', '1536-1284']

DOI: https://doi.org/10.1109/mwc.008.2200157