Modern communications are usually designed to pursue a higher bit-level precision and fewer bits while transmitting a message. This article rethinks these two major features and introduces the concept and advantage of semantics that characterizes a new kind of semantics-aware communication framework, incorporating both the semantic encoding and the semantic communication problem. After analyzing the underlying defects of existing semantics-aware techniques, we establish a confidence-based distillation mechanism for the joint semantics-noise coding (JSNC) problem and a reinforcement learning (RL)-powered semantic communication paradigm that endows a system the ability to convey the semantics instead of pursuing the bit level accuracy. On top of these technical contributions, this work provides a new insight to understand how the semantics are processed and represented in a semantics-aware coding and communication system, and verifies the significant benefits of doing so. Targeted on the next generation's semantics-aware communication, some critical concerns and open challenges such as the information overhead, semantic security and implementation cost are also discussed and envisioned.
@article{arxiv.2110.08496,
title = {Rethinking Modern Communication from Semantic Coding to Semantic Communication},
author = {Kun Lu and Qingyang Zhou and Rongpeng Li and Zhifeng Zhao and Xianfu Chen and Jianjun Wu and Honggang Zhang},
journal= {arXiv preprint arXiv:2110.08496},
year = {2022}
}