Learning Based Joint Coding-Modulation for Digital Semantic Communication Systems

Understand

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.