# Building Semantic Communication System via Molecules: An End-to-End Training Approach

arXiv: https://arxiv.org/abs/2404.09595 · HTML: https://mlsanity.com/paper/2404.09595/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 13 of its 40 references that are in the map.
- First posted on arXiv 15 Apr 2024.

## Builds on (most cited first, 13 of 13)

- [Beyond Transmitting Bits: Context, Semantics, and Task-Oriented Communications](https://mlsanity.com/paper/2207.09353/) (2022)
- [On the Road to 6G: Visions, Requirements, Key Technologies and Testbeds](https://mlsanity.com/paper/2302.14536/) (2023)
- [CDDM: Channel Denoising Diffusion Models for Wireless Semantic Communications](https://mlsanity.com/paper/2309.08895/) (2023)
- [Deep Joint Source-Channel Coding for Semantic Communications](https://mlsanity.com/paper/2211.08747/) (2022)
- [Model-free Training of End-to-end Communication Systems](https://mlsanity.com/paper/1812.05929/) (2018)
- [Approximating the Void: Learning Stochastic Channel Models from Observation with Variational Generative Adversarial Networks](https://mlsanity.com/paper/1805.06350/) (2018)
- [Deep Joint Source-Channel Coding for CSI Feedback: An End-to-End Approach](https://mlsanity.com/paper/2203.16005/) (2022)
- [A Novel Experimental Platform for In-Vessel Multi-Chemical Molecular Communications](https://mlsanity.com/paper/1704.04810/) (2017)
- [Encrypted Semantic Communication Using Adversarial Training for Privacy Preserving](https://mlsanity.com/paper/2209.09008/) (2022)
- [Deep Joint Source-Channel Coding for Image Transmission with Visual Protection](https://mlsanity.com/paper/2111.03234/) (2021)
- [Edge Semantic Cognitive Intelligence for 6G Networks: Novel Theoretical Models, Enabling Framework, and Typical Applications](https://mlsanity.com/paper/2205.12073/) (2022)
- [Novel Molecular Signaling Method and System for Molecular Communication in Human Body](https://mlsanity.com/paper/2003.01752/) (2020)
- [Fractionally-Spaced Equalization and Decision Feedback Sequence Detection for Diffusive MC](https://mlsanity.com/paper/2004.12735/) (2020)

## Built on by (most cited first, 2 of 2)

- [VideoQA-SC: Adaptive Semantic Communication for Video Question Answering](https://mlsanity.com/paper/2406.18538/) (2024)
- [Semantic Learning for Molecular Communication in Internet of Bio-Nano Things](https://mlsanity.com/paper/2502.08426/) (2025)

## Abstract (arXiv)

The concept of semantic communication provides a novel approach for applications in scenarios with limited communication resources. In this paper, we propose an end-to-end (E2E) semantic molecular communication system, aiming to enhance the efficiency of molecular communication systems by reducing the transmitted information. Specifically, following the joint source channel coding paradigm, the network is designed to encode the task-relevant information into the concentration of the information molecules, which is robust to the degradation of the molecular communication channel. Furthermore, we propose a channel network to enable the E2E learning over the non-differentiable molecular channel. Experimental results demonstrate the superior performance of the semantic molecular communication system over the conventional methods in classification tasks.