Semantic Communication with Memory

نویسندگان

چکیده

While semantic communication succeeds in efficiently transmitting due to the strong capability extract essential information, it is still far from intelligent or human-like communications. In this paper, we introduce an component, memory, into communications mimic human Particularly, investigate a deep learning (DL) based system with named Mem-DeepSC, by considering scenario question answer task. We exploit universal Transformer transceiver information and memory module process context information. Moreover, derive relationship between length of signal channel noise validate possibility dynamic transmission. Specially, propose two transmission methods enhance reliability as well reduce overheads masking some unessential elements, which are recognized through training model mutual Numerical results show that proposed Mem-DeepSC superior benchmarks terms accuracy efficiency, i.e., number transmitted symbols.

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ژورنال

عنوان ژورنال: IEEE Journal on Selected Areas in Communications

سال: 2023

ISSN: ['0733-8716', '1558-0008']

DOI: https://doi.org/10.1109/jsac.2023.3288236