Learning Based Joint Coding-Modulation for Digital Semantic
Communication Systems
- URL: http://arxiv.org/abs/2208.05704v1
- Date: Thu, 11 Aug 2022 08:58:35 GMT
- Title: Learning Based Joint Coding-Modulation for Digital Semantic
Communication Systems
- Authors: Yufei Bo, Yiheng Duan, Shuo Shao, Meixia Tao
- Abstract summary: In learning-based semantic communications, neural networks have replaced different building blocks in traditional communication systems.
The intrinsic mechanism of neural network based digital modulation is mapping continuous output of the neural network encoder into discrete constellation symbols.
We develop a joint coding-modulation scheme for digital semantic communications with BPSK modulation.
- Score: 45.81474044790071
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: In learning-based semantic communications, neural networks have replaced
different building blocks in traditional communication systems. However, the
digital modulation still remains a challenge for neural networks. The intrinsic
mechanism of neural network based digital modulation is mapping continuous
output of the neural network encoder into discrete constellation symbols, which
is a non-differentiable function that cannot be trained with existing gradient
descend algorithms. To overcome this challenge, in this paper we develop a
joint coding-modulation scheme for digital semantic communications with BPSK
modulation. In our method, the neural network outputs the likelihood of each
constellation point, instead of having a concrete mapping. A random code rather
than a deterministic code is hence used, which preserves more information for
the symbols with a close likelihood on each constellation point. The joint
coding-modulation design can match the modulation process with channel states,
and hence improve the performance of digital semantic communications.
Experiment results show that our method outperforms existing digital modulation
methods in semantic communications over a wide range of SNR, and outperforms
neural network based analog modulation method in low SNR regime.
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